From 42fca1a1cdbc2807bfddb750dcd9aef1cc6a42ac Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 24 Jul 2023 17:38:56 -0300 Subject: [PATCH 01/31] updating to libtorch v2.0.1 --- R/RcppExports.R | 940 +- R/gen-method.R | 95 +- R/gen-namespace.R | 1657 +- R/install.R | 2 +- inst/include/lantern/lantern.h | 765 +- man/torch_std.Rd | 8 +- man/torch_std_mean.Rd | 8 +- man/torch_symeig.Rd | 5 +- man/torch_var.Rd | 8 +- man/torch_var_mean.Rd | 8 +- src/RcppExports.cpp | 3509 +-- src/gen-namespace.cpp | 1315 +- src/lantern/CMakeLists.txt | 2 +- .../headers/declarations/declarations.yaml | 17724 +++++++++------- src/lantern/include/lantern/lantern.h | 765 +- src/lantern/src/Indexing.cpp | 14 +- src/lantern/src/Pickler.cpp | 2 +- src/lantern/src/Tensor.cpp | 6 +- src/lantern/src/lantern.cpp | 1744 +- tools/torchgen/R/cpp.R | 4 +- tools/torchgen/R/utils.R | 2 +- ...ns-1.13.1.yaml => Declarations-2.0.1.yaml} | 17724 +++++++++------- 22 files changed, 26472 insertions(+), 19835 deletions(-) rename tools/torchgen/inst/declaration/{Declarations-1.13.1.yaml => Declarations-2.0.1.yaml} (97%) diff --git a/R/RcppExports.R b/R/RcppExports.R index c88cb4d3bf..5c296e2802 100644 --- a/R/RcppExports.R +++ b/R/RcppExports.R @@ -545,6 +545,14 @@ cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor <- function(self, vec .Call(`_torch_cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor`, self, vec1, vec2, beta, alpha) } +cpp_torch_method__is_all_true_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_method__is_all_true_self_Tensor`, self) +} + +cpp_torch_method__is_any_true_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_method__is_any_true_self_Tensor`, self) +} + cpp_torch_method_all_self_Tensor_dim_int64_t <- function(self, dim, keepdim) { .Call(`_torch_cpp_torch_method_all_self_Tensor_dim_int64_t`, self, dim, keepdim) } @@ -1681,10 +1689,6 @@ cpp_torch_method_prelu_self_Tensor_weight_Tensor <- function(self, weight) { .Call(`_torch_cpp_torch_method_prelu_self_Tensor_weight_Tensor`, self, weight) } -cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor <- function(grad_output, self, weight) { - .Call(`_torch_cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor`, grad_output, self, weight) -} - cpp_torch_method_hardshrink_self_Tensor <- function(self, lambd) { .Call(`_torch_cpp_torch_method_hardshrink_self_Tensor`, self, lambd) } @@ -1849,6 +1853,10 @@ cpp_torch_method_squeeze_self_Tensor_dim_Dimname <- function(self, dim) { .Call(`_torch_cpp_torch_method_squeeze_self_Tensor_dim_Dimname`, self, dim) } +cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef <- function(self, dim) { + .Call(`_torch_cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef`, self, dim) +} + cpp_torch_method_squeeze__self_Tensor <- function(self) { .Call(`_torch_cpp_torch_method_squeeze__self_Tensor`, self) } @@ -1857,6 +1865,10 @@ cpp_torch_method_squeeze__self_Tensor_dim_int64_t <- function(self, dim) { .Call(`_torch_cpp_torch_method_squeeze__self_Tensor_dim_int64_t`, self, dim) } +cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef <- function(self, dim) { + .Call(`_torch_cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef`, self, dim) +} + cpp_torch_method_squeeze__self_Tensor_dim_Dimname <- function(self, dim) { .Call(`_torch_cpp_torch_method_squeeze__self_Tensor_dim_Dimname`, self, dim) } @@ -1925,18 +1937,10 @@ cpp_torch_method_std_self_Tensor_dim_IntArrayRef <- function(self, dim, unbiased .Call(`_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_method_std_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } -cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_method_prod_self_Tensor <- function(self, dtype) { .Call(`_torch_cpp_torch_method_prod_self_Tensor`, self, dtype) } @@ -2057,18 +2061,10 @@ cpp_torch_method_var_self_Tensor_dim_IntArrayRef <- function(self, dim, unbiased .Call(`_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_method_var_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } -cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_method_view_as_self_Tensor_other_Tensor <- function(self, other) { .Call(`_torch_cpp_torch_method_view_as_self_Tensor_other_Tensor`, self, other) } @@ -2077,6 +2073,10 @@ cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor <- function(con .Call(`_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor`, condition, self, other) } +cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar <- function(condition, self, other) { + .Call(`_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar`, condition, self, other) +} + cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType <- function(self, p, dtype) { .Call(`_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType`, self, p, dtype) } @@ -2273,24 +2273,24 @@ cpp_torch_method_to_sparse_self_Tensor_sparse_dim_int64_t <- function(self, spar .Call(`_torch_cpp_torch_method_to_sparse_self_Tensor_sparse_dim_int64_t`, self, sparse_dim) } -cpp_torch_method_to_sparse_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_method_to_sparse_self_Tensor`, self) +cpp_torch_method_to_sparse_self_Tensor <- function(self, layout, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_self_Tensor`, self, layout, blocksize, dense_dim) } -cpp_torch_method_to_sparse_csr_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_method_to_sparse_csr_self_Tensor`, self) +cpp_torch_method_to_sparse_csr_self_Tensor <- function(self, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_csr_self_Tensor`, self, dense_dim) } -cpp_torch_method_to_sparse_csc_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_method_to_sparse_csc_self_Tensor`, self) +cpp_torch_method_to_sparse_csc_self_Tensor <- function(self, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_csc_self_Tensor`, self, dense_dim) } -cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef <- function(self, blocksize) { - .Call(`_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef`, self, blocksize) +cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef <- function(self, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef`, self, blocksize, dense_dim) } -cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef <- function(self, blocksize) { - .Call(`_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef`, self, blocksize) +cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef <- function(self, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef`, self, blocksize, dense_dim) } cpp_torch_method_to_mkldnn_self_Tensor <- function(self, dtype) { @@ -3009,10 +3009,6 @@ cpp_torch_method_triangular_solve_self_Tensor_A_Tensor <- function(self, A, uppe .Call(`_torch_cpp_torch_method_triangular_solve_self_Tensor_A_Tensor`, self, A, upper, transpose, unitriangular) } -cpp_torch_method_symeig_self_Tensor <- function(self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_method_symeig_self_Tensor`, self, eigenvectors, upper) -} - cpp_torch_method_svd_self_Tensor <- function(self, some, compute_uv) { .Call(`_torch_cpp_torch_method_svd_self_Tensor`, self, some, compute_uv) } @@ -3417,10 +3413,6 @@ cpp_torch_method_to_padded_tensor_self_Tensor_padding_double <- function(self, p .Call(`_torch_cpp_torch_method_to_padded_tensor_self_Tensor_padding_double`, self, padding, output_size) } -cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double <- function(self, weight, bias, eps) { - .Call(`_torch_cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double`, self, weight, bias, eps) -} - cpp_torch_namespace__cast_Byte_self_Tensor <- function(self, non_blocking) { .Call(`_torch_cpp_torch_namespace__cast_Byte_self_Tensor`, self, non_blocking) } @@ -3773,6 +3765,18 @@ cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_size_IntArrayRef_ .Call(`_torch_cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_size_IntArrayRef_align_corners_bool`, grad, size, align_corners) } +cpp_torch_namespace__is_all_true_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_namespace__is_all_true_self_Tensor`, self) +} + +cpp_torch_namespace__is_any_true_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_namespace__is_any_true_self_Tensor`, self) +} + +cpp_torch_namespace__test_check_tensor_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_namespace__test_check_tensor_self_Tensor`, self) +} + cpp_torch_namespace_all_self_Tensor_dim_int64_t <- function(self, dim, keepdim) { .Call(`_torch_cpp_torch_namespace_all_self_Tensor_dim_int64_t`, self, dim, keepdim) } @@ -5729,12 +5733,8 @@ cpp_torch_namespace_max_pool2d_self_Tensor_kernel_size_IntArrayRef <- function(s .Call(`_torch_cpp_torch_namespace_max_pool2d_self_Tensor_kernel_size_IntArrayRef`, self, kernel_size, stride, padding, dilation, ceil_mode) } -cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef <- function(self, kernel_size, stride, padding, dilation, ceil_mode) { - .Call(`_torch_cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef`, self, kernel_size, stride, padding, dilation, ceil_mode) -} - -cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) { - .Call(`_torch_cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef`, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) +cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) { + .Call(`_torch_cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef`, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) } cpp_torch_namespace_mkldnn_max_pool2d_self_Tensor_kernel_size_IntArrayRef <- function(self, kernel_size, stride, padding, dilation, ceil_mode) { @@ -5869,6 +5869,14 @@ cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor_bias_Tensor_pad .Call(`_torch_cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t`, self, weight, bias, padding, stride, dilation, groups) } +cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool <- function(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) { + .Call(`_torch_cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool`, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) +} + +cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor <- function(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) { + .Call(`_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor`, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) +} + cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double <- function(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon) { .Call(`_torch_cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double`, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon) } @@ -5917,12 +5925,12 @@ cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor <- function(sparse, de .Call(`_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor`, sparse, dense) } -cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor <- function(self, other) { - .Call(`_torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor`, self, other) +cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view <- function(sparse, dense, reduce) { + .Call(`_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view`, sparse, dense, reduce) } -cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor <- function(t, mask_indices) { - .Call(`_torch_cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor`, t, mask_indices) +cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor`, self, other) } cpp_torch_namespace_mode_self_Tensor_dim_int64_t <- function(self, dim, keepdim) { @@ -6005,6 +6013,22 @@ cpp_torch_namespace_native_batch_norm_out_out_Tensor_save_mean_Tensor_save_invst .Call(`_torch_cpp_torch_namespace_native_batch_norm_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double`, out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps) } +cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double <- function(input, weight, bias, running_mean, running_var, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double`, input, weight, bias, running_mean, running_var, training, momentum, eps) +} + +cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double <- function(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double`, out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps) +} + +cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double <- function(input, weight, bias, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double`, input, weight, bias, training, momentum, eps) +} + +cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double <- function(out, save_mean, save_invstd, input, weight, bias, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double`, out, save_mean, save_invstd, input, weight, bias, training, momentum, eps) +} + cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double <- function(input, eps) { .Call(`_torch_cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double`, input, eps) } @@ -6353,6 +6377,10 @@ cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef <- function(self, shap .Call(`_torch_cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef`, self, shape) } +cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef <- function(self, size) { + .Call(`_torch_cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef`, self, size) +} + cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(self, size, stride) { .Call(`_torch_cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, self, size, stride) } @@ -6413,8 +6441,12 @@ cpp_torch_namespace_prelu_self_Tensor_weight_Tensor <- function(self, weight) { .Call(`_torch_cpp_torch_namespace_prelu_self_Tensor_weight_Tensor`, self, weight) } -cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor <- function(grad_output, self, weight) { - .Call(`_torch_cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor`, grad_output, self, weight) +cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor <- function(self, weight) { + .Call(`_torch_cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor`, self, weight) +} + +cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor <- function(grad_output, self, weight) { + .Call(`_torch_cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor`, grad_output, self, weight) } cpp_torch_namespace_gelu_out_out_Tensor_self_Tensor <- function(out, self, approximate) { @@ -6725,6 +6757,10 @@ cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname <- function(self, dim) { .Call(`_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname`, self, dim) } +cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef <- function(self, dim) { + .Call(`_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef`, self, dim) +} + cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor <- function(self, mat1, mat2, beta, alpha) { .Call(`_torch_cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor`, self, mat1, mat2, beta, alpha) } @@ -6853,10 +6889,6 @@ cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef <- function(self, dim, unbia .Call(`_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_std_mean_self_Tensor <- function(self, unbiased) { .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor`, self, unbiased) } @@ -6865,26 +6897,14 @@ cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef <- function(self, dim, .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef <- function(out, self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef`, out, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(out, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t`, out, self, dim, correction, keepdim) -} - cpp_torch_namespace_std_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } @@ -6893,14 +6913,6 @@ cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList <- function(o .Call(`_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList`, out, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - -cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t <- function(out, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t`, out, self, dim, correction, keepdim) -} - cpp_torch_namespace_prod_self_Tensor <- function(self, dtype) { .Call(`_torch_cpp_torch_namespace_prod_self_Tensor`, self, dtype) } @@ -7141,18 +7153,10 @@ cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef <- function(self, dim, unbia .Call(`_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef <- function(out, self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef`, out, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(out, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t`, out, self, dim, correction, keepdim) -} - cpp_torch_namespace_var_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } @@ -7161,14 +7165,6 @@ cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList <- function(o .Call(`_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList`, out, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - -cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t <- function(out, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t`, out, self, dim, correction, keepdim) -} - cpp_torch_namespace_var_mean_self_Tensor <- function(self, unbiased) { .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor`, self, unbiased) } @@ -7177,18 +7173,10 @@ cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef <- function(self, dim, .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor <- function(condition, self, other) { .Call(`_torch_cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor`, condition, self, other) } @@ -7397,10 +7385,6 @@ cpp_torch_namespace_frexp_out_mantissa_Tensor_exponent_Tensor_self_Tensor <- fun .Call(`_torch_cpp_torch_namespace_frexp_out_mantissa_Tensor_exponent_Tensor_self_Tensor`, mantissa, exponent, self) } -cpp_torch_namespace_frobenius_norm_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_namespace_frobenius_norm_self_Tensor`, self) -} - cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef <- function(self, dim, keepdim) { .Call(`_torch_cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef`, self, dim, keepdim) } @@ -7497,6 +7481,14 @@ cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor_mat2_Tensor <- .Call(`_torch_cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor_mat2_Tensor`, self, mat1, mat2, beta, alpha) } +cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view <- function(self, other, reduce) { + .Call(`_torch_cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view`, self, other, reduce) +} + +cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2 <- function(self, grad_out, weight, reduce, arg_out, output_mask) { + .Call(`_torch_cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2`, self, grad_out, weight, reduce, arg_out, output_mask) +} + cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor <- function(out, self, mat1, mat2, beta, alpha) { .Call(`_torch_cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor`, out, self, mat1, mat2, beta, alpha) } @@ -7653,8 +7645,8 @@ cpp_torch_namespace_unbind_self_Tensor_dim_Dimname <- function(self, dim) { .Call(`_torch_cpp_torch_namespace_unbind_self_Tensor_dim_Dimname`, self, dim) } -cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor <- function(self, padding, stride, dilation, groups) { - .Call(`_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor`, self, padding, stride, dilation, groups) +cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor <- function(self, padding, stride, dilation, groups, input_size) { + .Call(`_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor`, self, padding, stride, dilation, groups, input_size) } cpp_torch_namespace_mkldnn_reorder_conv3d_weight_self_Tensor <- function(self, padding, stride, dilation, groups) { @@ -7845,8 +7837,8 @@ cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_b .Call(`_torch_cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) } -cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - .Call(`_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) +cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + .Call(`_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) } cpp_torch_namespace__thnn_fused_lstm_cell_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor <- function(input_gates, hidden_gates, cx, input_bias, hidden_bias) { @@ -8241,10 +8233,6 @@ cpp_torch_namespace_diag_self_Tensor <- function(self, diagonal) { .Call(`_torch_cpp_torch_namespace_diag_self_Tensor`, self, diagonal) } -cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t <- function(grad, input_sizes, diagonal) { - .Call(`_torch_cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t`, grad, input_sizes, diagonal) -} - cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor <- function(out, self, other, dim) { .Call(`_torch_cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor`, out, self, other, dim) } @@ -8593,18 +8581,6 @@ cpp_torch_namespace_linalg_vander_x_Tensor <- function(x, False) { .Call(`_torch_cpp_torch_namespace_linalg_vander_x_Tensor`, x, False) } -cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor <- function(e, V, self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor`, e, V, self, eigenvectors, upper) -} - -cpp_torch_namespace_symeig_self_Tensor <- function(self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_namespace_symeig_self_Tensor`, self, eigenvectors, upper) -} - -cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool <- function(self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool`, self, eigenvectors, upper) -} - cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor <- function(U, S, V, self, some, compute_uv) { .Call(`_torch_cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor`, U, S, V, self, some, compute_uv) } @@ -8957,6 +8933,10 @@ cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor <- function(out, .Call(`_torch_cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor`, out, self, other) } +cpp_torch_namespace_max_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_max_out_out_Tensor_self_Tensor`, out, self) +} + cpp_torch_namespace_minimum_self_Tensor_other_Tensor <- function(self, other) { .Call(`_torch_cpp_torch_namespace_minimum_self_Tensor_other_Tensor`, self, other) } @@ -9209,6 +9189,38 @@ cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar <- function(self invisible(.Call(`_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar`, self, scalar)) } +cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar <- function(self, scalar) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar`, self, scalar) +} + +cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar <- function(self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar`, self, scalar)) +} + +cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar <- function(self, scalar) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar`, self, scalar) +} + +cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar <- function(self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar`, self, scalar)) +} + +cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar <- function(self, scalar) { + .Call(`_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar`, self, scalar) +} + +cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar <- function(self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar`, self, scalar)) +} + +cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar <- function(self, scalar) { + .Call(`_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar`, self, scalar) +} + +cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar <- function(self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar`, self, scalar)) +} + cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList <- function(self, other, alpha) { .Call(`_torch_cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList`, self, other, alpha) } @@ -9241,6 +9253,38 @@ cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList <- function(s invisible(.Call(`_torch_cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList`, self, other)) } +cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList`, self, other) +} + +cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList <- function(self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList`, self, other)) +} + +cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList`, self, other) +} + +cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList <- function(self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList`, self, other)) +} + +cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList`, self, other) +} + +cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList <- function(self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList`, self, other)) +} + +cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList`, self, other) +} + +cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList <- function(self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList`, self, other)) +} + cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { .Call(`_torch_cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar`, self, scalars) } @@ -9273,6 +9317,38 @@ cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar <- func invisible(.Call(`_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) } +cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar`, self, scalars) +} + +cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) +} + +cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar`, self, scalars) +} + +cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) +} + +cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar`, self, scalars) +} + +cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) +} + +cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar`, self, scalars) +} + +cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) +} + cpp_torch_namespace__foreach_exp_self_TensorList <- function(self) { .Call(`_torch_cpp_torch_namespace__foreach_exp_self_TensorList`, self) } @@ -9513,10 +9589,18 @@ cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2 invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, self, tensor1, tensor2, scalars)) } +cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, self, tensor1, tensor2, scalars)) +} + cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar <- function(self, tensor1, tensor2, scalars) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, self, tensor1, tensor2, scalars)) } +cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, self, tensor1, tensor2, scalars)) +} + cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList <- function(self, tensor1, tensor2, value) { .Call(`_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList`, self, tensor1, tensor2, value) } @@ -9529,28 +9613,36 @@ cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_ .Call(`_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, self, tensor1, tensor2, scalars) } +cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(self, tensor1, tensor2, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, self, tensor1, tensor2, scalars) +} + cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar <- function(self, tensor1, tensor2, scalars) { .Call(`_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, self, tensor1, tensor2, scalars) } -cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList <- function(self, other) { - .Call(`_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList`, self, other) +cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(self, tensor1, tensor2, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, self, tensor1, tensor2, scalars) } -cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList <- function(self, other) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList`, self, other)) +cpp_torch_namespace__foreach_norm_self_TensorList <- function(self, ord) { + .Call(`_torch_cpp_torch_namespace__foreach_norm_self_TensorList`, self, ord) } -cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList <- function(self, other) { - .Call(`_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList`, self, other) +cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList <- function(self, tensors1, weights) { + .Call(`_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList`, self, tensors1, weights) } -cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList <- function(self, other) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList`, self, other)) +cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList <- function(self, tensors1, weights) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList`, self, tensors1, weights)) } -cpp_torch_namespace__foreach_norm_self_TensorList <- function(self, ord) { - .Call(`_torch_cpp_torch_namespace__foreach_norm_self_TensorList`, self, ord) +cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar <- function(self, tensors1, weight) { + .Call(`_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar`, self, tensors1, weight) +} + +cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar <- function(self, tensors1, weight) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar`, self, tensors1, weight)) } cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor <- function(self, boundaries, out_int32, right) { @@ -9569,10 +9661,6 @@ cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Tensor <- function( .Call(`_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Tensor`, sorted_sequence, self, out_int32, right, side, sorter) } -cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor`, self) -} - cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor <- function(out, sorted_sequence, self, out_int32, right, side, sorter) { .Call(`_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor`, out, sorted_sequence, self, out_int32, right, side, sorter) } @@ -10253,50 +10341,26 @@ cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_IntArrayRef_align .Call(`_torch_cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(input, output_size, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } @@ -10305,14 +10369,6 @@ cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_output_size_IntArrayR .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } -cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - -cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(input, output_size, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } @@ -10321,14 +10377,6 @@ cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_output_size_IntArrayR .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } -cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - -cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(input, output_size, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } @@ -10337,14 +10385,6 @@ cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_output_size_IntArrayR .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } -cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - -cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool <- function(out, self, output_size, align_corners, scales) { .Call(`_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool`, out, self, output_size, align_corners, scales) } @@ -11753,6 +11793,10 @@ cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t <- function(self, dim) .Call(`_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t`, self, dim) } +cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef <- function(self, dim) { + .Call(`_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef`, self, dim) +} + cpp_torch_namespace_t_copy_self_Tensor <- function(self) { .Call(`_torch_cpp_torch_namespace_t_copy_self_Tensor`, self) } @@ -11801,6 +11845,18 @@ cpp_torch_namespace_unbind_copy_self_Tensor <- function(self, dim) { .Call(`_torch_cpp_torch_namespace_unbind_copy_self_Tensor`, self, dim) } +cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor <- function(out, self, dim) { + invisible(.Call(`_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor`, out, self, dim)) +} + +cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t <- function(out, self, split_size, dim) { + invisible(.Call(`_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t`, out, self, split_size, dim)) +} + +cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef <- function(out, self, split_sizes, dim) { + invisible(.Call(`_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef`, out, self, split_sizes, dim)) +} + cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef <- function(self, size) { .Call(`_torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef`, self, size) } @@ -11817,164 +11873,72 @@ cpp_torch_namespace_alias_copy_self_Tensor <- function(self) { .Call(`_torch_cpp_torch_namespace_alias_copy_self_Tensor`, self) } -cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t <- function(out, self, level) { - .Call(`_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t`, out, self, level) +cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor <- function(self, query) { + .Call(`_torch_cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor`, self, query) } -cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t <- function(out, primal, tangent, level) { - .Call(`_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t`, out, primal, tangent, level) +cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor <- function(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) { + .Call(`_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor`, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) } -cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor <- function(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type) { + .Call(`_torch_cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor`, query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type) } -cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, is_causal) { + .Call(`_torch_cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, is_causal) } -cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) } -cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, is_causal) { + .Call(`_torch_cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, is_causal) } -cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(out, self, size, stride, storage_offset) { - .Call(`_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, out, self, size, stride, storage_offset) +cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, is_causal, dropout_mask) } -cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size) { - .Call(`_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) +cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, dropout_p, is_causal, return_debug_mask) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, dropout_p, is_causal, return_debug_mask) } -cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor <- function(out, self, offset, dim1, dim2) { - .Call(`_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor`, out, self, offset, dim1, dim2) +cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t <- function(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t`, grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) } -cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size, implicit) { - .Call(`_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size, implicit) +cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool <- function(query, key, value, compute_log_sumexp, is_causal) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool`, query, key, value, compute_log_sumexp, is_causal) } -cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef <- function(out, self, dims) { - .Call(`_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef`, out, self, dims) +cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor <- function(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor`, grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs) } -cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(out, self, size, stride) { - .Call(`_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, out, self, size, stride) +cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, is_causal) { + .Call(`_torch_cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, is_causal) } -cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t <- function(out, self, dim, index) { - .Call(`_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t`, out, self, dim, index) +cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool <- function(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask) { + .Call(`_torch_cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool`, query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask) } -cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t <- function(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) { + .Call(`_torch_cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t`, grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) } -cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor <- function(out, self, dim, start, end, step) { - .Call(`_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor`, out, self, dim, start, end, step) +cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t <- function(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal) { + .Call(`_torch_cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t`, query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal) } -cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t <- function(out, self, split_size, dim) { - invisible(.Call(`_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t`, out, self, split_size, dim)) +cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor <- function(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs) { + .Call(`_torch_cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor`, grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs) } -cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef <- function(out, self, split_sizes, dim) { - invisible(.Call(`_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef`, out, self, split_sizes, dim)) -} - -cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t <- function(out, self, dim) { - .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t`, out, self, dim) -} - -cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t <- function(out, self, dim0, dim1) { - .Call(`_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t`, out, self, dim0, dim1) -} - -cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t <- function(out, self, dim) { - .Call(`_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t`, out, self, dim) -} - -cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor <- function(out, self, dim) { - invisible(.Call(`_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor`, out, self, dim)) -} - -cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size) { - .Call(`_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) -} - -cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType <- function(out, self, dtype) { - .Call(`_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType`, out, self, dtype) -} - -cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t <- function(out, self, dimension, size, step) { - .Call(`_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t`, out, self, dimension, size, step) -} - -cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor <- function(self, query) { - .Call(`_torch_cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor`, self, query) -} - -cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor <- function(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) { - .Call(`_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor`, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) -} - -cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor <- function(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type) { - .Call(`_torch_cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor`, query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type) -} - -cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) { - .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) -} - -cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) { - .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) -} - -cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) { - .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) -} - -cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor <- function(q, k, v, dropout_p) { - .Call(`_torch_cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor`, q, k, v, dropout_p) +cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor <- function(q, k, v, dropout_p) { + .Call(`_torch_cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor`, q, k, v, dropout_p) } cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor <- function(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask) { @@ -11989,10 +11953,6 @@ cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor <- function(out, x) .Call(`_torch_cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor`, out, x) } -cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool <- function(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal) { - .Call(`_torch_cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool`, query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal) -} - cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor <- function(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, incr_key, incr_value) { .Call(`_torch_cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor`, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, incr_key, incr_value) } @@ -12385,6 +12345,10 @@ cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_Tenso invisible(.Call(`_torch_cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf)) } +cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool <- function(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) { + invisible(.Call(`_torch_cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf)) +} + cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor <- function(out, self, other, self_num_batch_dims) { .Call(`_torch_cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor`, out, self, other, self_num_batch_dims) } @@ -12585,6 +12549,10 @@ cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targe .Call(`_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef`, out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity) } +cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor <- function(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity) { + .Call(`_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor`, out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity) +} + cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t <- function(out, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity) { .Call(`_torch_cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t`, out, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity) } @@ -12837,12 +12805,8 @@ cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor_dim_int64_t .Call(`_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor_dim_int64_t`, out0, out1, self, dim, keepdim) } -cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(out, self, kernel_size, stride, padding, dilation, ceil_mode) { - .Call(`_torch_cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef`, out, self, kernel_size, stride, padding, dilation, ceil_mode) -} - -cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) { - .Call(`_torch_cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef`, out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) +cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) { + .Call(`_torch_cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef`, out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) } cpp_torch_namespace_mkldnn_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(out, self, kernel_size, stride, padding, dilation, ceil_mode) { @@ -12889,6 +12853,14 @@ cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tensor_weight_Tensor_ .Call(`_torch_cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t`, out, self, weight, bias, padding, stride, dilation, groups) } +cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool <- function(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) { + .Call(`_torch_cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool`, out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) +} + +cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor <- function(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) { + .Call(`_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor`, out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) +} + cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double <- function(out0, out1, out2, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon) { .Call(`_torch_cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double`, out0, out1, out2, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon) } @@ -12921,14 +12893,14 @@ cpp_torch_namespace__sparse_sparse_matmul_out_out_Tensor_self_Tensor_other_Tenso .Call(`_torch_cpp_torch_namespace__sparse_sparse_matmul_out_out_Tensor_self_Tensor_other_Tensor`, out, self, other) } -cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor <- function(out, t, mask_indices) { - .Call(`_torch_cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor`, out, t, mask_indices) -} - cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar <- function(out, self, other) { .Call(`_torch_cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar`, out, self, other) } +cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double <- function(input, weight, bias, running_mean, running_var, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double`, input, weight, bias, running_mean, running_var, training, momentum, eps) +} + cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double <- function(out0, out1, input, eps) { .Call(`_torch_cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double`, out0, out1, input, eps) } @@ -13057,14 +13029,6 @@ cpp_torch_namespace_relu_out_out_Tensor_self_Tensor <- function(out, self) { .Call(`_torch_cpp_torch_namespace_relu_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor <- function(out, self, weight) { - .Call(`_torch_cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor`, out, self, weight) -} - -cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor <- function(out0, out1, grad_output, self, weight) { - .Call(`_torch_cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor`, out0, out1, grad_output, self, weight) -} - cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t <- function(out, grad_output, input_sizes, dim, index) { .Call(`_torch_cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t`, out, grad_output, input_sizes, dim, index) } @@ -13105,10 +13069,6 @@ cpp_torch_namespace_sum_out_out_Tensor_self_Tensor <- function(out, self, dtype) .Call(`_torch_cpp_torch_namespace_sum_out_out_Tensor_self_Tensor`, out, self, dtype) } -cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(out0, out1, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t`, out0, out1, self, dim, correction, keepdim) -} - cpp_torch_namespace_prod_out_out_Tensor_self_Tensor <- function(out, self, dtype) { .Call(`_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor`, out, self, dtype) } @@ -13185,10 +13145,6 @@ cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size_IntArrayRef <- .Call(`_torch_cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) } -cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(out0, out1, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t`, out0, out1, self, dim, correction, keepdim) -} - cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor <- function(out0, out1, v, g, dim) { .Call(`_torch_cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor`, out0, out1, v, g, dim) } @@ -13389,32 +13345,32 @@ cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor_sparse_dim_int64_t <- f .Call(`_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor_sparse_dim_int64_t`, out, self, sparse_dim) } -cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor <- function(out, self, layout, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor`, out, self, layout, blocksize, dense_dim) } -cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor <- function(out, self, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor`, out, self, dense_dim) } -cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor <- function(out, self, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor`, out, self, dense_dim) } -cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef <- function(out, self, blocksize) { - .Call(`_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef`, out, self, blocksize) +cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef <- function(out, self, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef`, out, self, blocksize, dense_dim) } -cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef <- function(out, self, blocksize) { - .Call(`_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef`, out, self, blocksize) +cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef <- function(out, self, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef`, out, self, blocksize, dense_dim) } cpp_torch_namespace_to_mkldnn_out_out_Tensor_self_Tensor <- function(out, self, dtype) { .Call(`_torch_cpp_torch_namespace_to_mkldnn_out_out_Tensor_self_Tensor`, out, self, dtype) } -cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor <- function(out, self, padding, stride, dilation, groups) { - .Call(`_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor`, out, self, padding, stride, dilation, groups) +cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor <- function(out, self, padding, stride, dilation, groups, input_size) { + .Call(`_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor`, out, self, padding, stride, dilation, groups, input_size) } cpp_torch_namespace_mkldnn_reorder_conv3d_weight_out_out_Tensor_self_Tensor <- function(out, self, padding, stride, dilation, groups) { @@ -13501,12 +13457,12 @@ cpp_torch_namespace__to_copy_out_out_Tensor_self_Tensor <- function(out, self, n .Call(`_torch_cpp_torch_namespace__to_copy_out_out_Tensor_self_Tensor`, out, self, non_blocking, memory_format) } -cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - .Call(`_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) +cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + .Call(`_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) } -cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - invisible(.Call(`_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)) +cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + invisible(.Call(`_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)) } cpp_torch_namespace__thnn_fused_lstm_cell_out_out0_Tensor_out1_Tensor_out2_Tensor_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor <- function(out0, out1, out2, input_gates, hidden_gates, cx, input_bias, hidden_bias) { @@ -13713,10 +13669,6 @@ cpp_torch_namespace_trace_out_out_Tensor_self_Tensor <- function(out, self) { .Call(`_torch_cpp_torch_namespace_trace_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool <- function(out0, out1, self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool`, out0, out1, self, eigenvectors, upper) -} - cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool <- function(out, self, A, upper) { .Call(`_torch_cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool`, out, self, A, upper) } @@ -13785,6 +13737,22 @@ cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_Scala invisible(.Call(`_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) } +cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar <- function(out, self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) +} + +cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar <- function(out, self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) +} + +cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar <- function(out, self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) +} + +cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar <- function(out, self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) +} + cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other, alpha) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other, alpha)) } @@ -13801,6 +13769,22 @@ cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_Tensor invisible(.Call(`_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) } +cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +} + +cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +} + +cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +} + +cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +} + cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) } @@ -13817,6 +13801,22 @@ cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars_Arra invisible(.Call(`_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) } +cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) +} + +cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) +} + +cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) +} + +cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) +} + cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList <- function(out, self) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList`, out, self)) } @@ -13949,28 +13949,32 @@ cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_ invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, out, self, tensor1, tensor2, scalars)) } -cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar <- function(out, self, tensor1, tensor2, scalars) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, out, self, tensor1, tensor2, scalars)) +cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(out, self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, out, self, tensor1, tensor2, scalars)) } -cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar <- function(out, self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, out, self, tensor1, tensor2, scalars)) } -cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(out, self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, out, self, tensor1, tensor2, scalars)) } cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList <- function(out, self, ord) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList`, out, self, ord)) } -cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor <- function(out, self, boundaries, out_int32, right) { - .Call(`_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor`, out, self, boundaries, out_int32, right) +cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList <- function(out, self, tensors1, weights) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList`, out, self, tensors1, weights)) +} + +cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar <- function(out, self, tensors1, weight) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar`, out, self, tensors1, weight)) } -cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor <- function(out, self, boundaries, out_int32, right) { + .Call(`_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor`, out, self, boundaries, out_int32, right) } cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar <- function(out, sorted_sequence, self, out_int32, right, side, sorter) { @@ -14013,160 +14017,172 @@ cpp_torch_namespace__adaptive_avg_pool3d_backward_out_out_Tensor_grad_output_Ten .Call(`_torch_cpp_torch_namespace__adaptive_avg_pool3d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor`, out, grad_output, self) } -cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 <- function(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask) { + .Call(`_torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3`, out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask) } -cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { + .Call(`_torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) } -cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { + .Call(`_torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) } -cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { + .Call(`_torch_cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) } -cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef <- function(out, values, addends) { + .Call(`_torch_cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef`, out, values, addends) } -cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef <- function(out, values, addends) { + .Call(`_torch_cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef`, out, values, addends) } -cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble <- function(out, values, addends) { + .Call(`_torch_cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble`, out, values, addends) } -cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view <- function(out, data, reduce, lengths, indices, offsets, axis, unsafe, initial) { + .Call(`_torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view`, out, data, reduce, lengths, indices, offsets, axis, unsafe, initial) } -cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view <- function(out, grad, output, data, reduce, lengths, offsets, axis, initial) { + .Call(`_torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view`, out, grad, output, data, reduce, lengths, offsets, axis, initial) } -cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList <- function(out, list, dtype, layout, device, pin_memory) { + .Call(`_torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList`, out, list, dtype, layout, device, pin_memory) } -cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t <- function(out, self, level) { + .Call(`_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t`, out, self, level) } -cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t <- function(out, primal, tangent, level) { + .Call(`_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t`, out, primal, tangent, level) } -cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(out, self, size, stride, storage_offset) { + .Call(`_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, out, self, size, stride, storage_offset) } -cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size) { + .Call(`_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) } -cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor <- function(out, self, offset, dim1, dim2) { + .Call(`_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor`, out, self, offset, dim1, dim2) } -cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 <- function(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask) { - .Call(`_torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3`, out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask) +cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size, implicit) { + .Call(`_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size, implicit) } -cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { - .Call(`_torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) +cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef <- function(out, self, dims) { + .Call(`_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef`, out, self, dims) } -cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { - .Call(`_torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) +cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(out, self, size, stride) { + .Call(`_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, out, self, size, stride) } -cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { - .Call(`_torch_cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) +cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t <- function(out, self, dim, index) { + .Call(`_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t`, out, self, dim, index) } -cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor <- function(out, self, dim, start, end, step) { + .Call(`_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor`, out, self, dim, start, end, step) } -cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef <- function(out, values, addends) { - .Call(`_torch_cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef`, out, values, addends) +cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef <- function(out, values, addends) { - .Call(`_torch_cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef`, out, values, addends) +cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t <- function(out, self, dim) { + .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t`, out, self, dim) } -cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble <- function(out, values, addends) { - .Call(`_torch_cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble`, out, values, addends) +cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef <- function(out, self, dim) { + .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef`, out, self, dim) } -cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t <- function(out, self, dim0, dim1) { + .Call(`_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t`, out, self, dim0, dim1) } -cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t <- function(out, self, dim) { + .Call(`_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t`, out, self, dim) } -cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view <- function(out, data, reduce, lengths, indices, offsets, axis, unsafe, initial) { - .Call(`_torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view`, out, data, reduce, lengths, indices, offsets, axis, unsafe, initial) +cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view <- function(out, grad, output, data, reduce, lengths, offsets, axis, initial) { - .Call(`_torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view`, out, grad, output, data, reduce, lengths, offsets, axis, initial) +cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList <- function(out, list, dtype, layout, device, pin_memory) { - .Call(`_torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList`, out, list, dtype, layout, device, pin_memory) +cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor`, out, self) +} + +cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor`, out, self) +} + +cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor`, out, self) +} + +cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor`, out, self) } cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { @@ -14177,12 +14193,24 @@ cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor <- function(out, .Call(`_torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double <- function(out, self, padding, output_size) { - .Call(`_torch_cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double`, out, self, padding, output_size) +cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size) { + .Call(`_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) } -cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double <- function(out, self, weight, bias, eps) { - .Call(`_torch_cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double`, out, self, weight, bias, eps) +cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType <- function(out, self, dtype) { + .Call(`_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType`, out, self, dtype) +} + +cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t <- function(out, self, dimension, size, step) { + .Call(`_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t`, out, self, dimension, size, step) +} + +cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor`, out, self) +} + +cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double <- function(out, self, padding, output_size) { + .Call(`_torch_cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double`, out, self, padding, output_size) } cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor <- function(out, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) { @@ -14221,6 +14249,14 @@ cpp_torch_namespace__fused_adam_self_TensorList_grads_TensorList_exp_avgs_Tensor .Call(`_torch_cpp_torch_namespace__fused_adam_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) } +cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool <- function(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) { + invisible(.Call(`_torch_cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf)) +} + +cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool <- function(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) { + .Call(`_torch_cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) +} + cpp_torch_generator <- function() { .Call(`_torch_cpp_torch_generator`) } diff --git a/R/gen-method.R b/R/gen-method.R index 064a0f424c..4298276b27 100644 --- a/R/gen-method.R +++ b/R/gen-method.R @@ -277,39 +277,52 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "_is_zerotensor", function() { args <- list() +Tensor$set("public", "_is_all_true", function() { args <- list() args <- c(list(self = self), args) expected_types <- list(self = "Tensor") nd_args <- "self" -return_types <- list(list('bool')) +return_types <- list(list('Tensor')) call_c_function( - fun_name = '_is_zerotensor', + fun_name = '_is_all_true', args = args, expected_types = expected_types, nd_args = nd_args, return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "_neg_view", function() { args <- list() +Tensor$set("public", "_is_any_true", function() { args <- list() args <- c(list(self = self), args) expected_types <- list(self = "Tensor") nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( - fun_name = '_neg_view', + fun_name = '_is_any_true', args = args, expected_types = expected_types, nd_args = nd_args, return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "_nested_tensor_layer_norm", function(weight, bias, eps) { args <- mget(x = c("weight", "bias", "eps")) +Tensor$set("public", "_is_zerotensor", function() { args <- list() args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", weight = "Tensor", bias = "Tensor", eps = "double") -nd_args <- c("self", "weight", "bias", "eps") +expected_types <- list(self = "Tensor") +nd_args <- "self" +return_types <- list(list('bool')) +call_c_function( + fun_name = '_is_zerotensor', + args = args, + expected_types = expected_types, + nd_args = nd_args, + return_types = return_types, + fun_type = 'method' +)}) +Tensor$set("public", "_neg_view", function() { args <- list() +args <- c(list(self = self), args) +expected_types <- list(self = "Tensor") +nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( - fun_name = '_nested_tensor_layer_norm', + fun_name = '_neg_view', args = args, expected_types = expected_types, nd_args = nd_args, @@ -5269,19 +5282,6 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "prelu_backward", function(grad_output, weight) { args <- mget(x = c("grad_output", "weight")) -args <- c(list(self = self), args) -expected_types <- list(grad_output = "Tensor", self = "Tensor", weight = "Tensor") -nd_args <- c("grad_output", "self", "weight") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( - fun_name = 'prelu_backward', - args = args, - expected_types = expected_types, - nd_args = nd_args, - return_types = return_types, - fun_type = 'method' -)}) Tensor$set("public", "prod", function(dim, keepdim = FALSE, dtype = NULL) { args <- mget(x = c("dim", "keepdim", "dtype")) args <- c(list(self = self), args) expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname"), keepdim = "bool", @@ -6417,7 +6417,8 @@ call_c_function( )}) Tensor$set("public", "squeeze", function(dim) { args <- mget(x = c("dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname")) +expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname", "IntArrayRef" +)) nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -6430,7 +6431,8 @@ call_c_function( )}) Tensor$set("public", "squeeze_", function(dim) { args <- mget(x = c("dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname")) +expected_types <- list(self = "Tensor", dim = c("int64_t", "IntArrayRef", "Dimname" +)) nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -6455,11 +6457,11 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "std", function(dim, correction, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "correction", "unbiased", "keepdim")) +Tensor$set("public", "std", function(dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "correction", "unbiased", "keepdim")) args <- c(list(self = self), args) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") +nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'std', @@ -6642,19 +6644,6 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "symeig", function(eigenvectors = FALSE, upper = TRUE) { args <- mget(x = c("eigenvectors", "upper")) -args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", eigenvectors = "bool", upper = "bool") -nd_args <- "self" -return_types <- list(list("Tensor", "Tensor")) -call_c_function( - fun_name = 'symeig', - args = args, - expected_types = expected_types, - nd_args = nd_args, - return_types = return_types, - fun_type = 'method' -)}) Tensor$set("public", "t", function() { args <- list() args <- c(list(self = self), args) expected_types <- list(self = "Tensor") @@ -6841,9 +6830,10 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse", function(sparse_dim) { args <- mget(x = c("sparse_dim")) +Tensor$set("public", "to_sparse", function(layout = NULL, sparse_dim, blocksize = NULL, dense_dim = NULL) { args <- mget(x = c("layout", "sparse_dim", "blocksize", "dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", sparse_dim = "int64_t") +expected_types <- list(self = "Tensor", layout = "Layout", sparse_dim = "int64_t", + blocksize = "IntArrayRef", dense_dim = "int64_t") nd_args <- c("self", "sparse_dim") return_types <- list(list('Tensor')) call_c_function( @@ -6854,9 +6844,9 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse_bsc", function(blocksize) { args <- mget(x = c("blocksize")) +Tensor$set("public", "to_sparse_bsc", function(blocksize, dense_dim = NULL) { args <- mget(x = c("blocksize", "dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", blocksize = "IntArrayRef") +expected_types <- list(self = "Tensor", blocksize = "IntArrayRef", dense_dim = "int64_t") nd_args <- c("self", "blocksize") return_types <- list(list('Tensor')) call_c_function( @@ -6867,9 +6857,9 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse_bsr", function(blocksize) { args <- mget(x = c("blocksize")) +Tensor$set("public", "to_sparse_bsr", function(blocksize, dense_dim = NULL) { args <- mget(x = c("blocksize", "dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", blocksize = "IntArrayRef") +expected_types <- list(self = "Tensor", blocksize = "IntArrayRef", dense_dim = "int64_t") nd_args <- c("self", "blocksize") return_types <- list(list('Tensor')) call_c_function( @@ -6880,9 +6870,9 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse_csc", function() { args <- list() +Tensor$set("public", "to_sparse_csc", function(dense_dim = NULL) { args <- mget(x = c("dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor") +expected_types <- list(self = "Tensor", dense_dim = "int64_t") nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( @@ -6893,9 +6883,9 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse_csr", function() { args <- list() +Tensor$set("public", "to_sparse_csr", function(dense_dim = NULL) { args <- mget(x = c("dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor") +expected_types <- list(self = "Tensor", dense_dim = "int64_t") nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( @@ -7223,11 +7213,11 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "var", function(dim, correction, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "correction", "unbiased", "keepdim")) +Tensor$set("public", "var", function(dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "correction", "unbiased", "keepdim")) args <- c(list(self = self), args) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") +nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'var', @@ -7291,7 +7281,8 @@ call_c_function( )}) Tensor$set("public", "where", function(condition, other) { args <- mget(x = c("condition", "other")) args <- c(list(self = self), args) -expected_types <- list(condition = "Tensor", self = "Tensor", other = "Tensor") +expected_types <- list(condition = "Tensor", self = "Tensor", other = c("Tensor", +"Scalar")) nd_args <- c("condition", "self", "other") return_types <- list(list('Tensor')) call_c_function( diff --git a/R/gen-namespace.R b/R/gen-namespace.R index 23596123a5..0998ba4317 100644 --- a/R/gen-namespace.R +++ b/R/gen-namespace.R @@ -844,6 +844,23 @@ fun_type = 'namespace' } +#' @rdname torch__chunk_grad_outputs_efficient_attention +torch__chunk_grad_outputs_efficient_attention <- function(query, key, value, is_causal = FALSE) { + args <- mget(x = c("query", "key", "value", "is_causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", is_causal = "bool") +nd_args <- c("query", "key", "value") +return_types <- list(list('bool')) +call_c_function( +fun_name = '_chunk_grad_outputs_efficient_attention', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__coalesce torch__coalesce <- function(self) { args <- mget(x = c("self")) @@ -1360,8 +1377,9 @@ fun_type = 'namespace' torch__ctc_loss_out <- function(out0, out1, log_probs, targets, input_lengths, target_lengths, blank = 0L, zero_infinity = FALSE) { args <- mget(x = c("out0", "out1", "log_probs", "targets", "input_lengths", "target_lengths", "blank", "zero_infinity")) expected_types <- list(out0 = "Tensor", out1 = "Tensor", log_probs = "Tensor", - targets = "Tensor", input_lengths = "IntArrayRef", target_lengths = "IntArrayRef", - blank = "int64_t", zero_infinity = "bool") + targets = "Tensor", input_lengths = c("IntArrayRef", "Tensor" + ), target_lengths = c("IntArrayRef", "Tensor"), blank = "int64_t", + zero_infinity = "bool") nd_args <- c("out0", "out1", "log_probs", "targets", "input_lengths", "target_lengths" ) return_types <- list(list("Tensor", "Tensor")) @@ -1770,6 +1788,45 @@ fun_type = 'namespace' } +#' @rdname torch__efficient_attention_backward +torch__efficient_attention_backward <- function(grad_out_, query, key, value, out, logsumexp, is_causal = FALSE, chunk_grad_outputs = FALSE) { + args <- mget(x = c("grad_out_", "query", "key", "value", "out", "logsumexp", "is_causal", "chunk_grad_outputs")) +expected_types <- list(grad_out_ = "Tensor", query = "Tensor", key = "Tensor", + value = "Tensor", out = "Tensor", logsumexp = "Tensor", is_causal = "bool", + chunk_grad_outputs = "bool") +nd_args <- c("grad_out_", "query", "key", "value", "out", "logsumexp") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_efficient_attention_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__efficient_attention_forward +torch__efficient_attention_forward <- function(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp = FALSE, causal = FALSE) { + args <- mget(x = c("query", "key", "value", "cu_seqlens_q", "cu_seqlens_k", "max_seqlen_q", "compute_log_sumexp", "causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", cu_seqlens_q = "Tensor", + cu_seqlens_k = "Tensor", max_seqlen_q = "int64_t", compute_log_sumexp = "bool", + causal = "bool") +nd_args <- c("query", "key", "value", "cu_seqlens_q", "cu_seqlens_k", "max_seqlen_q" +) +return_types <- list(list("Tensor", "Tensor")) +call_c_function( +fun_name = '_efficient_attention_forward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__efficientzerotensor torch__efficientzerotensor <- function(size, options = list()) { args <- mget(x = c("size", "options")) @@ -2384,17 +2441,40 @@ fun_type = 'namespace' } -#' @rdname torch__flash_scaled_dot_product_attention -torch__flash_scaled_dot_product_attention <- function(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal) { - args <- mget(x = c("query", "key", "value", "cum_seq_q", "cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal")) +#' @rdname torch__flash_attention_backward +torch__flash_attention_backward <- function(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) { + args <- mget(x = c("grad_out", "query", "key", "value", "out", "logsumexp", "cum_seq_q", "cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "philox_seed", "philox_offset")) +expected_types <- list(grad_out = "Tensor", query = "Tensor", key = "Tensor", value = "Tensor", + out = "Tensor", logsumexp = "Tensor", cum_seq_q = "Tensor", + cum_seq_k = "Tensor", max_q = "int64_t", max_k = "int64_t", + dropout_p = "double", is_causal = "bool", philox_seed = "int64_t", + philox_offset = "int64_t") +nd_args <- c("grad_out", "query", "key", "value", "out", "logsumexp", "cum_seq_q", +"cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "philox_seed", +"philox_offset") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_flash_attention_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__flash_attention_forward +torch__flash_attention_forward <- function(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask) { + args <- mget(x = c("query", "key", "value", "cum_seq_q", "cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "return_debug_mask")) expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", cum_seq_q = "Tensor", cum_seq_k = "Tensor", max_q = "int64_t", max_k = "int64_t", - dropout_p = "double", is_causal = "bool") + dropout_p = "double", is_causal = "bool", return_debug_mask = "bool") nd_args <- c("query", "key", "value", "cum_seq_q", "cum_seq_k", "max_q", -"max_k", "dropout_p", "is_causal") -return_types <- list(list('Tensor')) +"max_k", "dropout_p", "is_causal", "return_debug_mask") +return_types <- list(list("Tensor", "Tensor", "int64_t", "int64_t", "Tensor")) call_c_function( -fun_name = '_flash_scaled_dot_product_attention', +fun_name = '_flash_attention_forward', args = args, expected_types = expected_types, nd_args = nd_args, @@ -2599,7 +2679,7 @@ fun_type = 'namespace' torch__foreach_addcdiv <- function(self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(self = "TensorList", tensor1 = "TensorList", tensor2 = "TensorList", - scalars = "ArrayRef", value = "Scalar") + scalars = c("ArrayRef", "Tensor"), value = "Scalar") nd_args <- c("self", "tensor1", "tensor2", "scalars") return_types <- list(list('TensorList')) call_c_function( @@ -2617,7 +2697,7 @@ fun_type = 'namespace' torch__foreach_addcdiv_ <- function(self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(self = "TensorList", tensor1 = "TensorList", tensor2 = "TensorList", - scalars = "ArrayRef", value = "Scalar") + scalars = c("ArrayRef", "Tensor"), value = "Scalar") nd_args <- c("self", "tensor1", "tensor2", "scalars") return_types <- list(list("void")) call_c_function( @@ -2635,7 +2715,8 @@ fun_type = 'namespace' torch__foreach_addcdiv_out <- function(out, self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("out", "self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(out = "TensorList", self = "TensorList", tensor1 = "TensorList", - tensor2 = "TensorList", scalars = "ArrayRef", value = "Scalar") + tensor2 = "TensorList", scalars = c("ArrayRef", "Tensor" + ), value = "Scalar") nd_args <- c("out", "self", "tensor1", "tensor2", "scalars") return_types <- list(list("void")) call_c_function( @@ -2653,7 +2734,7 @@ fun_type = 'namespace' torch__foreach_addcmul <- function(self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(self = "TensorList", tensor1 = "TensorList", tensor2 = "TensorList", - scalars = "ArrayRef", value = "Scalar") + scalars = c("ArrayRef", "Tensor"), value = "Scalar") nd_args <- c("self", "tensor1", "tensor2", "scalars") return_types <- list(list('TensorList')) call_c_function( @@ -2671,7 +2752,7 @@ fun_type = 'namespace' torch__foreach_addcmul_ <- function(self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(self = "TensorList", tensor1 = "TensorList", tensor2 = "TensorList", - scalars = "ArrayRef", value = "Scalar") + scalars = c("ArrayRef", "Tensor"), value = "Scalar") nd_args <- c("self", "tensor1", "tensor2", "scalars") return_types <- list(list("void")) call_c_function( @@ -2689,7 +2770,8 @@ fun_type = 'namespace' torch__foreach_addcmul_out <- function(out, self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("out", "self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(out = "TensorList", self = "TensorList", tensor1 = "TensorList", - tensor2 = "TensorList", scalars = "ArrayRef", value = "Scalar") + tensor2 = "TensorList", scalars = c("ArrayRef", "Tensor" + ), value = "Scalar") nd_args <- c("out", "self", "tensor1", "tensor2", "scalars") return_types <- list(list("void")) call_c_function( @@ -2856,6 +2938,114 @@ fun_type = 'namespace' } +#' @rdname torch__foreach_clamp_max +torch__foreach_clamp_max <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") +return_types <- list(list('TensorList')) +call_c_function( +fun_name = '_foreach_clamp_max', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_max_ +torch__foreach_clamp_max_ <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_clamp_max_', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_max_out +torch__foreach_clamp_max_out <- function(out, self, other, scalar, scalars) { + args <- mget(x = c("out", "self", "other", "scalar", "scalars")) +expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList", + scalar = "Scalar", scalars = "ArrayRef") +nd_args <- c("out", "self", "other", "scalar", "scalars") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_clamp_max_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_min +torch__foreach_clamp_min <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") +return_types <- list(list('TensorList')) +call_c_function( +fun_name = '_foreach_clamp_min', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_min_ +torch__foreach_clamp_min_ <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_clamp_min_', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_min_out +torch__foreach_clamp_min_out <- function(out, self, other, scalar, scalars) { + args <- mget(x = c("out", "self", "other", "scalar", "scalars")) +expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList", + scalar = "Scalar", scalars = "ArrayRef") +nd_args <- c("out", "self", "other", "scalar", "scalars") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_clamp_min_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__foreach_cos torch__foreach_cos <- function(self) { args <- mget(x = c("self")) @@ -3318,6 +3508,60 @@ fun_type = 'namespace' } +#' @rdname torch__foreach_lerp +torch__foreach_lerp <- function(self, tensors1, weight, weights) { + args <- mget(x = c("self", "tensors1", "weight", "weights")) +expected_types <- list(self = "TensorList", tensors1 = "TensorList", weight = "Scalar", + weights = "TensorList") +nd_args <- c("self", "tensors1", "weight", "weights") +return_types <- list(list('TensorList')) +call_c_function( +fun_name = '_foreach_lerp', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_lerp_ +torch__foreach_lerp_ <- function(self, tensors1, weight, weights) { + args <- mget(x = c("self", "tensors1", "weight", "weights")) +expected_types <- list(self = "TensorList", tensors1 = "TensorList", weight = "Scalar", + weights = "TensorList") +nd_args <- c("self", "tensors1", "weight", "weights") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_lerp_', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_lerp_out +torch__foreach_lerp_out <- function(out, self, tensors1, weight, weights) { + args <- mget(x = c("out", "self", "tensors1", "weight", "weights")) +expected_types <- list(out = "TensorList", self = "TensorList", tensors1 = "TensorList", + weight = "Scalar", weights = "TensorList") +nd_args <- c("out", "self", "tensors1", "weight", "weights") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_lerp_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__foreach_lgamma torch__foreach_lgamma <- function(self) { args <- mget(x = c("self")) @@ -3574,10 +3818,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_maximum -torch__foreach_maximum <- function(self, other) { - args <- mget(x = c("self", "other")) -expected_types <- list(self = "TensorList", other = "TensorList") -nd_args <- c("self", "other") +torch__foreach_maximum <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") return_types <- list(list('TensorList')) call_c_function( fun_name = '_foreach_maximum', @@ -3591,10 +3836,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_maximum_ -torch__foreach_maximum_ <- function(self, other) { - args <- mget(x = c("self", "other")) -expected_types <- list(self = "TensorList", other = "TensorList") -nd_args <- c("self", "other") +torch__foreach_maximum_ <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") return_types <- list(list("void")) call_c_function( fun_name = '_foreach_maximum_', @@ -3608,10 +3854,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_maximum_out -torch__foreach_maximum_out <- function(out, self, other) { - args <- mget(x = c("out", "self", "other")) -expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList") -nd_args <- c("out", "self", "other") +torch__foreach_maximum_out <- function(out, self, other, scalar, scalars) { + args <- mget(x = c("out", "self", "other", "scalar", "scalars")) +expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList", + scalar = "Scalar", scalars = "ArrayRef") +nd_args <- c("out", "self", "other", "scalar", "scalars") return_types <- list(list("void")) call_c_function( fun_name = '_foreach_maximum_out', @@ -3625,10 +3872,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_minimum -torch__foreach_minimum <- function(self, other) { - args <- mget(x = c("self", "other")) -expected_types <- list(self = "TensorList", other = "TensorList") -nd_args <- c("self", "other") +torch__foreach_minimum <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") return_types <- list(list('TensorList')) call_c_function( fun_name = '_foreach_minimum', @@ -3642,10 +3890,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_minimum_ -torch__foreach_minimum_ <- function(self, other) { - args <- mget(x = c("self", "other")) -expected_types <- list(self = "TensorList", other = "TensorList") -nd_args <- c("self", "other") +torch__foreach_minimum_ <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") return_types <- list(list("void")) call_c_function( fun_name = '_foreach_minimum_', @@ -3659,10 +3908,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_minimum_out -torch__foreach_minimum_out <- function(out, self, other) { - args <- mget(x = c("out", "self", "other")) -expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList") -nd_args <- c("out", "self", "other") +torch__foreach_minimum_out <- function(out, self, other, scalar, scalars) { + args <- mget(x = c("out", "self", "other", "scalar", "scalars")) +expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList", + scalar = "Scalar", scalars = "ArrayRef") +nd_args <- c("out", "self", "other", "scalar", "scalars") return_types <- list(list("void")) call_c_function( fun_name = '_foreach_minimum_out', @@ -4450,6 +4700,78 @@ fun_type = 'namespace' } +#' @rdname torch__fused_adamw +torch__fused_adamw <- function(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale = list(), found_inf = list()) { + args <- mget(x = c("self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", "state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", "amsgrad", "maximize", "grad_scale", "found_inf")) +expected_types <- list(self = "TensorList", grads = "TensorList", exp_avgs = "TensorList", + exp_avg_sqs = "TensorList", max_exp_avg_sqs = "TensorList", + state_steps = "TensorList", lr = "double", beta1 = "double", + beta2 = "double", weight_decay = "double", eps = "double", + amsgrad = "bool", maximize = "bool", grad_scale = "Tensor", + found_inf = "Tensor") +nd_args <- c("self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", +"state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", +"amsgrad", "maximize") +return_types <- list(list("TensorList", "TensorList", "TensorList", "TensorList", "TensorList")) +call_c_function( +fun_name = '_fused_adamw', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__fused_adamw_ +torch__fused_adamw_ <- function(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale = list(), found_inf = list()) { + args <- mget(x = c("self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", "state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", "amsgrad", "maximize", "grad_scale", "found_inf")) +expected_types <- list(self = "TensorList", grads = "TensorList", exp_avgs = "TensorList", + exp_avg_sqs = "TensorList", max_exp_avg_sqs = "TensorList", + state_steps = "TensorList", lr = "double", beta1 = "double", + beta2 = "double", weight_decay = "double", eps = "double", + amsgrad = "bool", maximize = "bool", grad_scale = "Tensor", + found_inf = "Tensor") +nd_args <- c("self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", +"state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", +"amsgrad", "maximize") +return_types <- list(list("void")) +call_c_function( +fun_name = '_fused_adamw_', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__fused_adamw_out +torch__fused_adamw_out <- function(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale = list(), found_inf = list()) { + args <- mget(x = c("out", "self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", "state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", "amsgrad", "maximize", "grad_scale", "found_inf")) +expected_types <- list(out = "TensorList", self = "TensorList", grads = "TensorList", + exp_avgs = "TensorList", exp_avg_sqs = "TensorList", max_exp_avg_sqs = "TensorList", + state_steps = "TensorList", lr = "double", beta1 = "double", + beta2 = "double", weight_decay = "double", eps = "double", + amsgrad = "bool", maximize = "bool", grad_scale = "Tensor", + found_inf = "Tensor") +nd_args <- c("out", "self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", +"state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", +"amsgrad", "maximize") +return_types <- list(list("void")) +call_c_function( +fun_name = '_fused_adamw_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__fused_dropout torch__fused_dropout <- function(self, p, generator = NULL) { args <- mget(x = c("self", "p", "generator")) @@ -4554,6 +4876,24 @@ fun_type = 'namespace' } +#' @rdname torch__fused_sdp_choice +torch__fused_sdp_choice <- function(query, key, value, attn_mask = list(), dropout_p = 0L, is_causal = FALSE) { + args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "is_causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", attn_mask = "Tensor", + dropout_p = "double", is_causal = "bool") +nd_args <- c("query", "key", "value") +return_types <- list(list('int64_t')) +call_c_function( +fun_name = '_fused_sdp_choice', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__fw_primal_copy torch__fw_primal_copy <- function(self, level) { args <- mget(x = c("self", "level")) @@ -4893,6 +5233,40 @@ fun_type = 'namespace' } +#' @rdname torch__is_all_true +torch__is_all_true <- function(self) { + args <- mget(x = c("self")) +expected_types <- list(self = "Tensor") +nd_args <- "self" +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_is_all_true', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__is_any_true +torch__is_any_true <- function(self) { + args <- mget(x = c("self")) +expected_types <- list(self = "Tensor") +nd_args <- "self" +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_is_any_true', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__is_zerotensor torch__is_zerotensor <- function(self) { args <- mget(x = c("self")) @@ -5231,7 +5605,7 @@ expected_types <- list(input = "Tensor", hx = "TensorList", params = "TensorList train = "bool", bidirectional = "bool", batch_first = "bool") nd_args <- c("input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first") -return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) call_c_function( fun_name = '_lstm_mps', args = args, @@ -5244,16 +5618,17 @@ fun_type = 'namespace' #' @rdname torch__lstm_mps_out -torch__lstm_mps_out <- function(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - args <- mget(x = c("out0", "out1", "out2", "out3", "out4", "input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) +torch__lstm_mps_out <- function(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + args <- mget(x = c("out0", "out1", "out2", "out3", "out4", "out5", "input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) expected_types <- list(out0 = "Tensor", out1 = "Tensor", out2 = "Tensor", out3 = "Tensor", - out4 = "Tensor", input = "Tensor", hx = "TensorList", params = "TensorList", - has_biases = "bool", num_layers = "int64_t", dropout = "double", - train = "bool", bidirectional = "bool", batch_first = "bool") -nd_args <- c("out0", "out1", "out2", "out3", "out4", "input", "hx", "params", -"has_biases", "num_layers", "dropout", "train", "bidirectional", + out4 = "Tensor", out5 = "Tensor", input = "Tensor", hx = "TensorList", + params = "TensorList", has_biases = "bool", num_layers = "int64_t", + dropout = "double", train = "bool", bidirectional = "bool", + batch_first = "bool") +nd_args <- c("out0", "out1", "out2", "out3", "out4", "out5", "input", "hx", +"params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first") -return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) call_c_function( fun_name = '_lstm_mps_out', args = args, @@ -5672,15 +6047,17 @@ fun_type = 'namespace' } -#' @rdname torch__mps_max_pool2d -torch__mps_max_pool2d <- function(self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { - args <- mget(x = c("self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) -expected_types <- list(self = "Tensor", kernel_size = "IntArrayRef", stride = "IntArrayRef", - padding = "IntArrayRef", dilation = "IntArrayRef", ceil_mode = "bool") -nd_args <- c("self", "kernel_size") -return_types <- list(list('Tensor')) +#' @rdname torch__native_batch_norm_legit +torch__native_batch_norm_legit <- function(input, weight, bias, running_mean, running_var, training, momentum, eps) { + args <- mget(x = c("input", "weight", "bias", "running_mean", "running_var", "training", "momentum", "eps")) +expected_types <- list(input = "Tensor", weight = "Tensor", bias = "Tensor", running_mean = "Tensor", + running_var = "Tensor", training = "bool", momentum = "double", + eps = "double") +nd_args <- c("input", "weight", "bias", "running_mean", "running_var", "training", +"momentum", "eps") +return_types <- list(list("Tensor", "Tensor", "Tensor")) call_c_function( -fun_name = '_mps_max_pool2d', +fun_name = '_native_batch_norm_legit', args = args, expected_types = expected_types, nd_args = nd_args, @@ -5690,16 +6067,38 @@ fun_type = 'namespace' } -#' @rdname torch__mps_max_pool2d_out -torch__mps_max_pool2d_out <- function(out, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { - args <- mget(x = c("out", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) -expected_types <- list(out = "Tensor", self = "Tensor", kernel_size = "IntArrayRef", - stride = "IntArrayRef", padding = "IntArrayRef", dilation = "IntArrayRef", - ceil_mode = "bool") -nd_args <- c("out", "self", "kernel_size") -return_types <- list(list('Tensor')) +#' @rdname torch__native_batch_norm_legit_functional +torch__native_batch_norm_legit_functional <- function(input, weight, bias, running_mean, running_var, training, momentum, eps) { + args <- mget(x = c("input", "weight", "bias", "running_mean", "running_var", "training", "momentum", "eps")) +expected_types <- list(input = "Tensor", weight = "Tensor", bias = "Tensor", running_mean = "Tensor", + running_var = "Tensor", training = "bool", momentum = "double", + eps = "double") +nd_args <- c("input", "weight", "bias", "running_mean", "running_var", "training", +"momentum", "eps") +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) call_c_function( -fun_name = '_mps_max_pool2d_out', +fun_name = '_native_batch_norm_legit_functional', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__native_batch_norm_legit_out +torch__native_batch_norm_legit_out <- function(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps) { + args <- mget(x = c("out", "save_mean", "save_invstd", "input", "weight", "bias", "running_mean", "running_var", "training", "momentum", "eps")) +expected_types <- list(out = "Tensor", save_mean = "Tensor", save_invstd = "Tensor", + input = "Tensor", weight = "Tensor", bias = "Tensor", running_mean = "Tensor", + running_var = "Tensor", training = "bool", momentum = "double", + eps = "double") +nd_args <- c("out", "save_mean", "save_invstd", "input", "weight", "bias", +"running_mean", "running_var", "training", "momentum", "eps") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_native_batch_norm_legit_out', args = args, expected_types = expected_types, nd_args = nd_args, @@ -6041,24 +6440,6 @@ fun_type = 'namespace' } -#' @rdname torch__nested_tensor_layer_norm_out -torch__nested_tensor_layer_norm_out <- function(out, self, weight, bias, eps) { - args <- mget(x = c("out", "self", "weight", "bias", "eps")) -expected_types <- list(out = "Tensor", self = "Tensor", weight = "Tensor", bias = "Tensor", - eps = "double") -nd_args <- c("out", "self", "weight", "bias", "eps") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = '_nested_tensor_layer_norm_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch__nested_tensor_size_out torch__nested_tensor_size_out <- function(out, self) { args <- mget(x = c("out", "self")) @@ -6444,6 +6825,40 @@ fun_type = 'namespace' } +#' @rdname torch__prelu_kernel +torch__prelu_kernel <- function(self, weight) { + args <- mget(x = c("self", "weight")) +expected_types <- list(self = "Tensor", weight = "Tensor") +nd_args <- c("self", "weight") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_prelu_kernel', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__prelu_kernel_backward +torch__prelu_kernel_backward <- function(grad_output, self, weight) { + args <- mget(x = c("grad_output", "self", "weight")) +expected_types <- list(grad_output = "Tensor", self = "Tensor", weight = "Tensor") +nd_args <- c("grad_output", "self", "weight") +return_types <- list(list("Tensor", "Tensor")) +call_c_function( +fun_name = '_prelu_kernel_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__remove_batch_dim torch__remove_batch_dim <- function(self, level, batch_size, out_dim) { args <- mget(x = c("self", "level", "batch_size", "out_dim")) @@ -6513,6 +6928,23 @@ fun_type = 'namespace' } +#' @rdname torch__reshape_copy +torch__reshape_copy <- function(self, size) { + args <- mget(x = c("self", "size")) +expected_types <- list(self = "Tensor", size = "IntArrayRef") +nd_args <- c("self", "size") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_reshape_copy', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__reshape_from_tensor torch__reshape_from_tensor <- function(self, shape) { args <- mget(x = c("self", "shape")) @@ -6667,15 +7099,15 @@ fun_type = 'namespace' } -#' @rdname torch__scaled_dot_product_attention_forward -torch__scaled_dot_product_attention_forward <- function(query, key, value, attn_mask = list(), dropout_p = 0L, need_attn_weights = FALSE, is_causal = FALSE) { - args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "need_attn_weights", "is_causal")) +#' @rdname torch__scaled_dot_product_attention_math +torch__scaled_dot_product_attention_math <- function(query, key, value, attn_mask = list(), dropout_p = 0L, is_causal = FALSE, dropout_mask = list()) { + args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "is_causal", "dropout_mask")) expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", attn_mask = "Tensor", - dropout_p = "double", need_attn_weights = "bool", is_causal = "bool") + dropout_p = "double", is_causal = "bool", dropout_mask = "Tensor") nd_args <- c("query", "key", "value") return_types <- list(list("Tensor", "Tensor")) call_c_function( -fun_name = '_scaled_dot_product_attention_forward', +fun_name = '_scaled_dot_product_attention_math', args = args, expected_types = expected_types, nd_args = nd_args, @@ -6685,15 +7117,75 @@ fun_type = 'namespace' } -#' @rdname torch__scaled_dot_product_attention_math -torch__scaled_dot_product_attention_math <- function(query, key, value, attn_mask = list(), dropout_p = 0L, need_attn_weights = FALSE, is_causal = FALSE) { - args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "need_attn_weights", "is_causal")) -expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", attn_mask = "Tensor", - dropout_p = "double", need_attn_weights = "bool", is_causal = "bool") -nd_args <- c("query", "key", "value") +#' @rdname torch__scaled_dot_product_efficient_attention +torch__scaled_dot_product_efficient_attention <- function(query, key, value, compute_log_sumexp, is_causal = FALSE) { + args <- mget(x = c("query", "key", "value", "compute_log_sumexp", "is_causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", compute_log_sumexp = "bool", + is_causal = "bool") +nd_args <- c("query", "key", "value", "compute_log_sumexp") return_types <- list(list("Tensor", "Tensor")) call_c_function( -fun_name = '_scaled_dot_product_attention_math', +fun_name = '_scaled_dot_product_efficient_attention', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__scaled_dot_product_efficient_attention_backward +torch__scaled_dot_product_efficient_attention_backward <- function(grad_out_, query, key, value, out, logsumexp, is_causal = FALSE, chunk_grad_outputs = FALSE) { + args <- mget(x = c("grad_out_", "query", "key", "value", "out", "logsumexp", "is_causal", "chunk_grad_outputs")) +expected_types <- list(grad_out_ = "Tensor", query = "Tensor", key = "Tensor", + value = "Tensor", out = "Tensor", logsumexp = "Tensor", is_causal = "bool", + chunk_grad_outputs = "bool") +nd_args <- c("grad_out_", "query", "key", "value", "out", "logsumexp") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_scaled_dot_product_efficient_attention_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__scaled_dot_product_flash_attention +torch__scaled_dot_product_flash_attention <- function(query, key, value, dropout_p = 0L, is_causal = FALSE, return_debug_mask = FALSE) { + args <- mget(x = c("query", "key", "value", "dropout_p", "is_causal", "return_debug_mask")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", dropout_p = "double", + is_causal = "bool", return_debug_mask = "bool") +nd_args <- c("query", "key", "value") +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "int64_t", "int64_t", "int64_t", "int64_t", "Tensor")) +call_c_function( +fun_name = '_scaled_dot_product_flash_attention', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__scaled_dot_product_flash_attention_backward +torch__scaled_dot_product_flash_attention_backward <- function(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) { + args <- mget(x = c("grad_out", "query", "key", "value", "out", "logsumexp", "cum_seq_q", "cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "philox_seed", "philox_offset")) +expected_types <- list(grad_out = "Tensor", query = "Tensor", key = "Tensor", value = "Tensor", + out = "Tensor", logsumexp = "Tensor", cum_seq_q = "Tensor", + cum_seq_k = "Tensor", max_q = "int64_t", max_k = "int64_t", + dropout_p = "double", is_causal = "bool", philox_seed = "int64_t", + philox_offset = "int64_t") +nd_args <- c("grad_out", "query", "key", "value", "out", "logsumexp", "cum_seq_q", +"cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "philox_seed", +"philox_offset") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_scaled_dot_product_flash_attention_backward', args = args, expected_types = expected_types, nd_args = nd_args, @@ -7392,14 +7884,14 @@ fun_type = 'namespace' } -#' @rdname torch__sparse_mask_helper -torch__sparse_mask_helper <- function(t, mask_indices) { - args <- mget(x = c("t", "mask_indices")) -expected_types <- list(t = "Tensor", mask_indices = "Tensor") -nd_args <- c("t", "mask_indices") +#' @rdname torch__sparse_mm +torch__sparse_mm <- function(sparse, dense, reduce) { + args <- mget(x = c("sparse", "dense", "reduce")) +expected_types <- list(sparse = "Tensor", dense = "Tensor", reduce = "c10::string_view") +nd_args <- c("sparse", "dense", "reduce") return_types <- list(list('Tensor')) call_c_function( -fun_name = '_sparse_mask_helper', +fun_name = '_sparse_mm', args = args, expected_types = expected_types, nd_args = nd_args, @@ -7409,14 +7901,14 @@ fun_type = 'namespace' } -#' @rdname torch__sparse_mask_helper_out -torch__sparse_mask_helper_out <- function(out, t, mask_indices) { - args <- mget(x = c("out", "t", "mask_indices")) -expected_types <- list(out = "Tensor", t = "Tensor", mask_indices = "Tensor") -nd_args <- c("out", "t", "mask_indices") -return_types <- list(list('Tensor')) +#' @rdname torch__sparse_mm_reduce_impl +torch__sparse_mm_reduce_impl <- function(self, other, reduce) { + args <- mget(x = c("self", "other", "reduce")) +expected_types <- list(self = "Tensor", other = "Tensor", reduce = "c10::string_view") +nd_args <- c("self", "other", "reduce") +return_types <- list(list("Tensor", "Tensor")) call_c_function( -fun_name = '_sparse_mask_helper_out', +fun_name = '_sparse_mm_reduce_impl', args = args, expected_types = expected_types, nd_args = nd_args, @@ -7426,14 +7918,16 @@ fun_type = 'namespace' } -#' @rdname torch__sparse_mm -torch__sparse_mm <- function(sparse, dense) { - args <- mget(x = c("sparse", "dense")) -expected_types <- list(sparse = "Tensor", dense = "Tensor") -nd_args <- c("sparse", "dense") -return_types <- list(list('Tensor')) +#' @rdname torch__sparse_mm_reduce_impl_backward +torch__sparse_mm_reduce_impl_backward <- function(self, grad_out, weight, reduce, arg_out, output_mask) { + args <- mget(x = c("self", "grad_out", "weight", "reduce", "arg_out", "output_mask")) +expected_types <- list(self = "Tensor", grad_out = "Tensor", weight = "Tensor", + reduce = "c10::string_view", arg_out = "Tensor", output_mask = "::std::array") +nd_args <- c("self", "grad_out", "weight", "reduce", "arg_out", "output_mask" +) +return_types <- list(list("Tensor", "Tensor")) call_c_function( -fun_name = '_sparse_mm', +fun_name = '_sparse_mm_reduce_impl_backward', args = args, expected_types = expected_types, nd_args = nd_args, @@ -7754,41 +8248,6 @@ fun_type = 'namespace' } -#' @rdname torch__symeig_helper -torch__symeig_helper <- function(self, eigenvectors, upper) { - args <- mget(x = c("self", "eigenvectors", "upper")) -expected_types <- list(self = "Tensor", eigenvectors = "bool", upper = "bool") -nd_args <- c("self", "eigenvectors", "upper") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = '_symeig_helper', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch__symeig_helper_out -torch__symeig_helper_out <- function(out0, out1, self, eigenvectors, upper) { - args <- mget(x = c("out0", "out1", "self", "eigenvectors", "upper")) -expected_types <- list(out0 = "Tensor", out1 = "Tensor", self = "Tensor", eigenvectors = "bool", - upper = "bool") -nd_args <- c("out0", "out1", "self", "eigenvectors", "upper") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = '_symeig_helper_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch__test_autograd_multiple_dispatch torch__test_autograd_multiple_dispatch <- function(self, b) { args <- mget(x = c("self", "b")) @@ -7874,6 +8333,23 @@ fun_type = 'namespace' } +#' @rdname torch__test_check_tensor +torch__test_check_tensor <- function(self) { + args <- mget(x = c("self")) +expected_types <- list(self = "Tensor") +nd_args <- "self" +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_test_check_tensor', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__test_optional_filled_intlist torch__test_optional_filled_intlist <- function(values, addends) { args <- mget(x = c("values", "addends")) @@ -8304,40 +8780,6 @@ fun_type = 'namespace' } -#' @rdname torch__torch_cuda_cu_linker_symbol_op -torch__torch_cuda_cu_linker_symbol_op <- function(self) { - args <- mget(x = c("self")) -expected_types <- list(self = "Tensor") -nd_args <- "self" -return_types <- list(list('Tensor')) -call_c_function( -fun_name = '_torch_cuda_cu_linker_symbol_op', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch__torch_cuda_cu_linker_symbol_op_out -torch__torch_cuda_cu_linker_symbol_op_out <- function(out, self) { - args <- mget(x = c("out", "self")) -expected_types <- list(out = "Tensor", self = "Tensor") -nd_args <- c("out", "self") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = '_torch_cuda_cu_linker_symbol_op_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch__transform_bias_rescale_qkv torch__transform_bias_rescale_qkv <- function(qkv, qkv_bias, num_heads) { args <- mget(x = c("qkv", "qkv_bias", "num_heads")) @@ -8737,13 +9179,12 @@ fun_type = 'namespace' #' @rdname torch__upsample_bicubic2d_aa_backward -torch__upsample_bicubic2d_aa_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) +torch__upsample_bicubic2d_aa_backward <- function(grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bicubic2d_aa_backward', @@ -8757,14 +9198,13 @@ fun_type = 'namespace' #' @rdname torch__upsample_bicubic2d_aa_backward_out -torch__upsample_bicubic2d_aa_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch__upsample_bicubic2d_aa_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bicubic2d_aa_backward_out', @@ -8778,13 +9218,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_bicubic2d_aa_out -torch__upsample_bicubic2d_aa_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch__upsample_bicubic2d_aa_out <- function(out, self, output_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bicubic2d_aa_out', @@ -8818,13 +9256,12 @@ fun_type = 'namespace' #' @rdname torch__upsample_bilinear2d_aa_backward -torch__upsample_bilinear2d_aa_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) +torch__upsample_bilinear2d_aa_backward <- function(grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bilinear2d_aa_backward', @@ -8838,14 +9275,13 @@ fun_type = 'namespace' #' @rdname torch__upsample_bilinear2d_aa_backward_out -torch__upsample_bilinear2d_aa_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch__upsample_bilinear2d_aa_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bilinear2d_aa_backward_out', @@ -8859,13 +9295,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_bilinear2d_aa_out -torch__upsample_bilinear2d_aa_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch__upsample_bilinear2d_aa_out <- function(out, self, output_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bilinear2d_aa_out', @@ -8897,12 +9331,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact1d_backward -torch__upsample_nearest_exact1d_backward <- function(grad_output, output_size, input_size, scale_factors, scales = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales")) +torch__upsample_nearest_exact1d_backward <- function(grad_output, output_size, input_size, scales = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact1d_backward', @@ -8916,13 +9349,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact1d_backward_out -torch__upsample_nearest_exact1d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch__upsample_nearest_exact1d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact1d_backward_out', @@ -8936,11 +9367,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact1d_out -torch__upsample_nearest_exact1d_out <- function(out, input, self, output_size, scale_factors, scales = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch__upsample_nearest_exact1d_out <- function(out, self, output_size, scales = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact1d_out', @@ -8973,13 +9404,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact2d_backward -torch__upsample_nearest_exact2d_backward <- function(grad_output, output_size, input_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales_h", "scales_w")) +torch__upsample_nearest_exact2d_backward <- function(grad_output, output_size, input_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact2d_backward', @@ -8993,14 +9422,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact2d_backward_out -torch__upsample_nearest_exact2d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch__upsample_nearest_exact2d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales_h = "double", scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact2d_backward_out', @@ -9014,12 +9440,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact2d_out -torch__upsample_nearest_exact2d_out <- function(out, input, self, output_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch__upsample_nearest_exact2d_out <- function(out, self, output_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact2d_out', @@ -9052,13 +9477,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact3d_backward -torch__upsample_nearest_exact3d_backward <- function(grad_output, output_size, input_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales_d", "scales_h", "scales_w")) +torch__upsample_nearest_exact3d_backward <- function(grad_output, output_size, input_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales_d", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales_d = "double", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact3d_backward', @@ -9072,14 +9495,12 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact3d_backward_out -torch__upsample_nearest_exact3d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch__upsample_nearest_exact3d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales_d", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales_d = "double", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact3d_backward_out', @@ -9093,12 +9514,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact3d_out -torch__upsample_nearest_exact3d_out <- function(out, input, self, output_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch__upsample_nearest_exact3d_out <- function(out, self, output_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales_d", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales_d = "double", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact3d_out', @@ -15173,23 +15593,6 @@ fun_type = 'namespace' } -#' @rdname torch_diag_backward -torch_diag_backward <- function(grad, input_sizes, diagonal) { - args <- mget(x = c("grad", "input_sizes", "diagonal")) -expected_types <- list(grad = "Tensor", input_sizes = "IntArrayRef", diagonal = "int64_t") -nd_args <- c("grad", "input_sizes", "diagonal") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = 'diag_backward', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_diag_embed torch_diag_embed <- function(self, offset = 0L, dim1 = -2L, dim2 = -1L) { args <- mget(x = c("self", "offset", "dim1", "dim2")) @@ -23991,16 +24394,16 @@ fun_type = 'namespace' #' @rdname torch_lstm_mps_backward -torch_lstm_mps_backward <- function(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - args <- mget(x = c("grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", "input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) +torch_lstm_mps_backward <- function(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + args <- mget(x = c("grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", "input", "layersOutputs", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) expected_types <- list(grad_y = "Tensor", grad_hy = "Tensor", grad_cy = "Tensor", z_state = "Tensor", cell_state_fwd = "Tensor", input = "Tensor", - hx = "TensorList", params = "TensorList", has_biases = "bool", - num_layers = "int64_t", dropout = "double", train = "bool", - bidirectional = "bool", batch_first = "bool") + layersOutputs = "Tensor", hx = "TensorList", params = "TensorList", + has_biases = "bool", num_layers = "int64_t", dropout = "double", + train = "bool", bidirectional = "bool", batch_first = "bool") nd_args <- c("grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", -"input", "hx", "params", "has_biases", "num_layers", "dropout", -"train", "bidirectional", "batch_first") +"input", "layersOutputs", "hx", "params", "has_biases", "num_layers", +"dropout", "train", "bidirectional", "batch_first") return_types <- list(list("Tensor", "TensorList", "TensorList")) call_c_function( fun_name = 'lstm_mps_backward', @@ -24014,17 +24417,18 @@ fun_type = 'namespace' #' @rdname torch_lstm_mps_backward_out -torch_lstm_mps_backward_out <- function(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - args <- mget(x = c("out0", "out1", "out2", "grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", "input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) +torch_lstm_mps_backward_out <- function(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + args <- mget(x = c("out0", "out1", "out2", "grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", "input", "layersOutputs", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) expected_types <- list(out0 = "Tensor", out1 = "TensorList", out2 = "TensorList", grad_y = "Tensor", grad_hy = "Tensor", grad_cy = "Tensor", z_state = "Tensor", cell_state_fwd = "Tensor", input = "Tensor", - hx = "TensorList", params = "TensorList", has_biases = "bool", - num_layers = "int64_t", dropout = "double", train = "bool", - bidirectional = "bool", batch_first = "bool") + layersOutputs = "Tensor", hx = "TensorList", params = "TensorList", + has_biases = "bool", num_layers = "int64_t", dropout = "double", + train = "bool", bidirectional = "bool", batch_first = "bool") nd_args <- c("out0", "out1", "out2", "grad_y", "grad_hy", "grad_cy", "z_state", -"cell_state_fwd", "input", "hx", "params", "has_biases", "num_layers", -"dropout", "train", "bidirectional", "batch_first") +"cell_state_fwd", "input", "layersOutputs", "hx", "params", "has_biases", +"num_layers", "dropout", "train", "bidirectional", "batch_first" +) return_types <- list(list("void")) call_c_function( fun_name = 'lstm_mps_backward_out', @@ -24508,6 +24912,44 @@ fun_type = 'namespace' } +#' @rdname torch_max_pool2d_backward +torch_max_pool2d_backward <- function(grad_output, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { + args <- mget(x = c("grad_output", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) +expected_types <- list(grad_output = "Tensor", self = "Tensor", kernel_size = "IntArrayRef", + stride = "IntArrayRef", padding = "IntArrayRef", dilation = "IntArrayRef", + ceil_mode = "bool") +nd_args <- c("grad_output", "self", "kernel_size") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = 'max_pool2d_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch_max_pool2d_backward_out +torch_max_pool2d_backward_out <- function(out, grad_output, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { + args <- mget(x = c("out", "grad_output", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) +expected_types <- list(out = "Tensor", grad_output = "Tensor", self = "Tensor", + kernel_size = "IntArrayRef", stride = "IntArrayRef", padding = "IntArrayRef", + dilation = "IntArrayRef", ceil_mode = "bool") +nd_args <- c("out", "grad_output", "self", "kernel_size") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = 'max_pool2d_backward_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname .torch_max_pool2d_with_indices .torch_max_pool2d_with_indices <- function(self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { args <- mget(x = c("self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) @@ -25758,10 +26200,10 @@ fun_type = 'namespace' #' @rdname torch_mkldnn_reorder_conv2d_weight -torch_mkldnn_reorder_conv2d_weight <- function(self, padding = 0L, stride = 1L, dilation = 1L, groups = 1L) { - args <- mget(x = c("self", "padding", "stride", "dilation", "groups")) +torch_mkldnn_reorder_conv2d_weight <- function(self, padding = 0L, stride = 1L, dilation = 1L, groups = 1L, input_size = NULL) { + args <- mget(x = c("self", "padding", "stride", "dilation", "groups", "input_size")) expected_types <- list(self = "Tensor", padding = "IntArrayRef", stride = "IntArrayRef", - dilation = "IntArrayRef", groups = "int64_t") + dilation = "IntArrayRef", groups = "int64_t", input_size = "IntArrayRef") nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( @@ -25776,10 +26218,11 @@ fun_type = 'namespace' #' @rdname torch_mkldnn_reorder_conv2d_weight_out -torch_mkldnn_reorder_conv2d_weight_out <- function(out, self, padding = 0L, stride = 1L, dilation = 1L, groups = 1L) { - args <- mget(x = c("out", "self", "padding", "stride", "dilation", "groups")) +torch_mkldnn_reorder_conv2d_weight_out <- function(out, self, padding = 0L, stride = 1L, dilation = 1L, groups = 1L, input_size = NULL) { + args <- mget(x = c("out", "self", "padding", "stride", "dilation", "groups", "input_size")) expected_types <- list(out = "Tensor", self = "Tensor", padding = "IntArrayRef", - stride = "IntArrayRef", dilation = "IntArrayRef", groups = "int64_t") + stride = "IntArrayRef", dilation = "IntArrayRef", groups = "int64_t", + input_size = "IntArrayRef") nd_args <- c("out", "self") return_types <- list(list('Tensor')) call_c_function( @@ -25829,6 +26272,111 @@ fun_type = 'namespace' } +#' @rdname torch_mkldnn_rnn_layer +torch_mkldnn_rnn_layer <- function(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) { + args <- mget(x = c("input", "weight0", "weight1", "weight2", "weight3", "hx_", "cx_", "reverse", "batch_sizes", "mode", "hidden_size", "num_layers", "has_biases", "bidirectional", "batch_first", "train")) +expected_types <- list(input = "Tensor", weight0 = "Tensor", weight1 = "Tensor", + weight2 = "Tensor", weight3 = "Tensor", hx_ = "Tensor", cx_ = "Tensor", + reverse = "bool", batch_sizes = "IntArrayRef", mode = "int64_t", + hidden_size = "int64_t", num_layers = "int64_t", has_biases = "bool", + bidirectional = "bool", batch_first = "bool", train = "bool") +nd_args <- c("input", "weight0", "weight1", "weight2", "weight3", "hx_", +"cx_", "reverse", "batch_sizes", "mode", "hidden_size", "num_layers", +"has_biases", "bidirectional", "batch_first", "train") +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = 'mkldnn_rnn_layer', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch_mkldnn_rnn_layer_backward +torch_mkldnn_rnn_layer_backward <- function(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) { + args <- mget(x = c("input", "weight1", "weight2", "weight3", "weight4", "hx_", "cx_tmp", "output", "hy_", "cy_", "grad_output", "grad_hy", "grad_cy", "reverse", "mode", "hidden_size", "num_layers", "has_biases", "train", "bidirectional", "batch_sizes", "batch_first", "workspace")) +expected_types <- list(input = "Tensor", weight1 = "Tensor", weight2 = "Tensor", + weight3 = "Tensor", weight4 = "Tensor", hx_ = "Tensor", cx_tmp = "Tensor", + output = "Tensor", hy_ = "Tensor", cy_ = "Tensor", grad_output = "Tensor", + grad_hy = "Tensor", grad_cy = "Tensor", reverse = "bool", + mode = "int64_t", hidden_size = "int64_t", num_layers = "int64_t", + has_biases = "bool", train = "bool", bidirectional = "bool", + batch_sizes = "IntArrayRef", batch_first = "bool", workspace = "Tensor") +nd_args <- c("input", "weight1", "weight2", "weight3", "weight4", "hx_", +"cx_tmp", "output", "hy_", "cy_", "grad_output", "grad_hy", "grad_cy", +"reverse", "mode", "hidden_size", "num_layers", "has_biases", +"train", "bidirectional", "batch_sizes", "batch_first", "workspace" +) +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = 'mkldnn_rnn_layer_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch_mkldnn_rnn_layer_backward_out +torch_mkldnn_rnn_layer_backward_out <- function(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) { + args <- mget(x = c("out0", "out1", "out2", "out3", "out4", "out5", "out6", "input", "weight1", "weight2", "weight3", "weight4", "hx_", "cx_tmp", "output", "hy_", "cy_", "grad_output", "grad_hy", "grad_cy", "reverse", "mode", "hidden_size", "num_layers", "has_biases", "train", "bidirectional", "batch_sizes", "batch_first", "workspace")) +expected_types <- list(out0 = "Tensor", out1 = "Tensor", out2 = "Tensor", out3 = "Tensor", + out4 = "Tensor", out5 = "Tensor", out6 = "Tensor", input = "Tensor", + weight1 = "Tensor", weight2 = "Tensor", weight3 = "Tensor", + weight4 = "Tensor", hx_ = "Tensor", cx_tmp = "Tensor", output = "Tensor", + hy_ = "Tensor", cy_ = "Tensor", grad_output = "Tensor", grad_hy = "Tensor", + grad_cy = "Tensor", reverse = "bool", mode = "int64_t", hidden_size = "int64_t", + num_layers = "int64_t", has_biases = "bool", train = "bool", + bidirectional = "bool", batch_sizes = "IntArrayRef", batch_first = "bool", + workspace = "Tensor") +nd_args <- c("out0", "out1", "out2", "out3", "out4", "out5", "out6", "input", +"weight1", "weight2", "weight3", "weight4", "hx_", "cx_tmp", +"output", "hy_", "cy_", "grad_output", "grad_hy", "grad_cy", +"reverse", "mode", "hidden_size", "num_layers", "has_biases", +"train", "bidirectional", "batch_sizes", "batch_first", "workspace" +) +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = 'mkldnn_rnn_layer_backward_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch_mkldnn_rnn_layer_out +torch_mkldnn_rnn_layer_out <- function(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) { + args <- mget(x = c("out0", "out1", "out2", "out3", "input", "weight0", "weight1", "weight2", "weight3", "hx_", "cx_", "reverse", "batch_sizes", "mode", "hidden_size", "num_layers", "has_biases", "bidirectional", "batch_first", "train")) +expected_types <- list(out0 = "Tensor", out1 = "Tensor", out2 = "Tensor", out3 = "Tensor", + input = "Tensor", weight0 = "Tensor", weight1 = "Tensor", + weight2 = "Tensor", weight3 = "Tensor", hx_ = "Tensor", cx_ = "Tensor", + reverse = "bool", batch_sizes = "IntArrayRef", mode = "int64_t", + hidden_size = "int64_t", num_layers = "int64_t", has_biases = "bool", + bidirectional = "bool", batch_first = "bool", train = "bool") +nd_args <- c("out0", "out1", "out2", "out3", "input", "weight0", "weight1", +"weight2", "weight3", "hx_", "cx_", "reverse", "batch_sizes", +"mode", "hidden_size", "num_layers", "has_biases", "bidirectional", +"batch_first", "train") +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = 'mkldnn_rnn_layer_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch_mm torch_mm <- function(self, mat2) { args <- mget(x = c("self", "mat2")) @@ -26018,44 +26566,6 @@ fun_type = 'namespace' } -#' @rdname torch_mps_max_pool2d_backward -torch_mps_max_pool2d_backward <- function(grad_output, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { - args <- mget(x = c("grad_output", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) -expected_types <- list(grad_output = "Tensor", self = "Tensor", kernel_size = "IntArrayRef", - stride = "IntArrayRef", padding = "IntArrayRef", dilation = "IntArrayRef", - ceil_mode = "bool") -nd_args <- c("grad_output", "self", "kernel_size") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = 'mps_max_pool2d_backward', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch_mps_max_pool2d_backward_out -torch_mps_max_pool2d_backward_out <- function(out, grad_output, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { - args <- mget(x = c("out", "grad_output", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) -expected_types <- list(out = "Tensor", grad_output = "Tensor", self = "Tensor", - kernel_size = "IntArrayRef", stride = "IntArrayRef", padding = "IntArrayRef", - dilation = "IntArrayRef", ceil_mode = "bool") -nd_args <- c("out", "grad_output", "self", "kernel_size") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = 'mps_max_pool2d_backward_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_mse_loss torch_mse_loss <- function(self, target, reduction = torch_reduction_mean()) { args <- mget(x = c("self", "target", "reduction")) @@ -28438,58 +28948,6 @@ fun_type = 'namespace' } -#' @rdname torch_prelu_backward -torch_prelu_backward <- function(grad_output, self, weight) { - args <- mget(x = c("grad_output", "self", "weight")) -expected_types <- list(grad_output = "Tensor", self = "Tensor", weight = "Tensor") -nd_args <- c("grad_output", "self", "weight") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'prelu_backward', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch_prelu_backward_out -torch_prelu_backward_out <- function(out0, out1, grad_output, self, weight) { - args <- mget(x = c("out0", "out1", "grad_output", "self", "weight")) -expected_types <- list(out0 = "Tensor", out1 = "Tensor", grad_output = "Tensor", - self = "Tensor", weight = "Tensor") -nd_args <- c("out0", "out1", "grad_output", "self", "weight") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'prelu_backward_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch_prelu_out -torch_prelu_out <- function(out, self, weight) { - args <- mget(x = c("out", "self", "weight")) -expected_types <- list(out = "Tensor", self = "Tensor", weight = "Tensor") -nd_args <- c("out", "self", "weight") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = 'prelu_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_prod torch_prod <- function(self, dim, keepdim = FALSE, dtype = NULL) { args <- mget(x = c("self", "dim", "keepdim", "dtype")) @@ -30875,6 +31333,24 @@ fun_type = 'namespace' } +#' @rdname torch_scaled_dot_product_attention +torch_scaled_dot_product_attention <- function(query, key, value, attn_mask = list(), dropout_p = 0L, is_causal = FALSE) { + args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "is_causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", attn_mask = "Tensor", + dropout_p = "double", is_causal = "bool") +nd_args <- c("query", "key", "value") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = 'scaled_dot_product_attention', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch_scatter torch_scatter <- function(self, dim, index, src, value, reduce) { args <- mget(x = c("self", "dim", "index", "src", "value", "reduce")) @@ -34782,7 +35258,8 @@ fun_type = 'namespace' #' @rdname torch_squeeze torch_squeeze <- function(self, dim) { args <- mget(x = c("self", "dim")) -expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname")) +expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname", "IntArrayRef" +)) nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -34799,7 +35276,7 @@ fun_type = 'namespace' #' @rdname torch_squeeze_copy torch_squeeze_copy <- function(self, dim) { args <- mget(x = c("self", "dim")) -expected_types <- list(self = "Tensor", dim = "int64_t") +expected_types <- list(self = "Tensor", dim = c("int64_t", "IntArrayRef")) nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -34816,7 +35293,8 @@ fun_type = 'namespace' #' @rdname torch_squeeze_copy_out torch_squeeze_copy_out <- function(out, self, dim) { args <- mget(x = c("out", "self", "dim")) -expected_types <- list(out = "Tensor", self = "Tensor", dim = "int64_t") +expected_types <- list(out = "Tensor", self = "Tensor", dim = c("int64_t", "IntArrayRef" +)) nd_args <- c("out", "self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -34901,11 +35379,11 @@ fun_type = 'namespace' #' @rdname torch_std -torch_std <- function(self, dim, correction, unbiased = TRUE, keepdim = FALSE) { +torch_std <- function(self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") +nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'std', @@ -34919,11 +35397,11 @@ fun_type = 'namespace' #' @rdname torch_std_mean -torch_std_mean <- function(self, dim, correction, unbiased = TRUE, keepdim = FALSE) { +torch_std_mean <- function(self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") +nd_args <- c("self", "dim") return_types <- list(list("Tensor", "Tensor")) call_c_function( fun_name = 'std_mean', @@ -34937,11 +35415,11 @@ fun_type = 'namespace' #' @rdname torch_std_mean_out -torch_std_mean_out <- function(out0, out1, self, dim, correction, keepdim = FALSE) { +torch_std_mean_out <- function(out0, out1, self, dim = NULL, correction = NULL, keepdim = FALSE) { args <- mget(x = c("out0", "out1", "self", "dim", "correction", "keepdim")) expected_types <- list(out0 = "Tensor", out1 = "Tensor", self = "Tensor", dim = "IntArrayRef", correction = "int64_t", keepdim = "bool") -nd_args <- c("out0", "out1", "self", "dim", "correction") +nd_args <- c("out0", "out1", "self") return_types <- list(list("Tensor", "Tensor")) call_c_function( fun_name = 'std_mean_out', @@ -34955,11 +35433,11 @@ fun_type = 'namespace' #' @rdname torch_std_out -torch_std_out <- function(out, self, dim, correction, unbiased = TRUE, keepdim = FALSE) { +torch_std_out <- function(out, self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("out", "self", "dim", "correction", "unbiased", "keepdim")) expected_types <- list(out = "Tensor", self = "Tensor", dim = c("IntArrayRef", "DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("out", "self", "dim", "correction") +nd_args <- c("out", "self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'std_out', @@ -35183,41 +35661,6 @@ fun_type = 'namespace' } -#' @rdname torch_symeig -torch_symeig <- function(self, eigenvectors = FALSE, upper = TRUE) { - args <- mget(x = c("self", "eigenvectors", "upper")) -expected_types <- list(self = "Tensor", eigenvectors = "bool", upper = "bool") -nd_args <- "self" -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'symeig', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch_symeig_out -torch_symeig_out <- function(e, V, self, eigenvectors = FALSE, upper = TRUE) { - args <- mget(x = c("e", "V", "self", "eigenvectors", "upper")) -expected_types <- list(e = "Tensor", V = "Tensor", self = "Tensor", eigenvectors = "bool", - upper = "bool") -nd_args <- c("e", "V", "self") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'symeig_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_t torch_t <- function(self) { args <- mget(x = c("self")) @@ -35736,9 +36179,10 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_bsc_out -torch_to_sparse_bsc_out <- function(out, self, blocksize) { - args <- mget(x = c("out", "self", "blocksize")) -expected_types <- list(out = "Tensor", self = "Tensor", blocksize = "IntArrayRef") +torch_to_sparse_bsc_out <- function(out, self, blocksize, dense_dim = NULL) { + args <- mget(x = c("out", "self", "blocksize", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", blocksize = "IntArrayRef", + dense_dim = "int64_t") nd_args <- c("out", "self", "blocksize") return_types <- list(list('Tensor')) call_c_function( @@ -35753,9 +36197,10 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_bsr_out -torch_to_sparse_bsr_out <- function(out, self, blocksize) { - args <- mget(x = c("out", "self", "blocksize")) -expected_types <- list(out = "Tensor", self = "Tensor", blocksize = "IntArrayRef") +torch_to_sparse_bsr_out <- function(out, self, blocksize, dense_dim = NULL) { + args <- mget(x = c("out", "self", "blocksize", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", blocksize = "IntArrayRef", + dense_dim = "int64_t") nd_args <- c("out", "self", "blocksize") return_types <- list(list('Tensor')) call_c_function( @@ -35770,9 +36215,9 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_csc_out -torch_to_sparse_csc_out <- function(out, self) { - args <- mget(x = c("out", "self")) -expected_types <- list(out = "Tensor", self = "Tensor") +torch_to_sparse_csc_out <- function(out, self, dense_dim = NULL) { + args <- mget(x = c("out", "self", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", dense_dim = "int64_t") nd_args <- c("out", "self") return_types <- list(list('Tensor')) call_c_function( @@ -35787,9 +36232,9 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_csr_out -torch_to_sparse_csr_out <- function(out, self) { - args <- mget(x = c("out", "self")) -expected_types <- list(out = "Tensor", self = "Tensor") +torch_to_sparse_csr_out <- function(out, self, dense_dim = NULL) { + args <- mget(x = c("out", "self", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", dense_dim = "int64_t") nd_args <- c("out", "self") return_types <- list(list('Tensor')) call_c_function( @@ -35804,9 +36249,10 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_out -torch_to_sparse_out <- function(out, self, sparse_dim) { - args <- mget(x = c("out", "self", "sparse_dim")) -expected_types <- list(out = "Tensor", self = "Tensor", sparse_dim = "int64_t") +torch_to_sparse_out <- function(out, self, layout = NULL, sparse_dim, blocksize = NULL, dense_dim = NULL) { + args <- mget(x = c("out", "self", "layout", "sparse_dim", "blocksize", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", layout = "Layout", sparse_dim = "int64_t", + blocksize = "IntArrayRef", dense_dim = "int64_t") nd_args <- c("out", "self", "sparse_dim") return_types <- list(list('Tensor')) call_c_function( @@ -36730,13 +37176,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_bicubic2d_backward -torch_upsample_bicubic2d_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) +torch_upsample_bicubic2d_backward <- function(grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bicubic2d_backward', @@ -36750,14 +37195,13 @@ fun_type = 'namespace' #' @rdname torch_upsample_bicubic2d_backward_out -torch_upsample_bicubic2d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch_upsample_bicubic2d_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bicubic2d_backward_out', @@ -36771,13 +37215,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_bicubic2d_out -torch_upsample_bicubic2d_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch_upsample_bicubic2d_out <- function(out, self, output_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bicubic2d_out', @@ -36811,13 +37253,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_bilinear2d_backward -torch_upsample_bilinear2d_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) +torch_upsample_bilinear2d_backward <- function(grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bilinear2d_backward', @@ -36831,14 +37272,13 @@ fun_type = 'namespace' #' @rdname torch_upsample_bilinear2d_backward_out -torch_upsample_bilinear2d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch_upsample_bilinear2d_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bilinear2d_backward_out', @@ -36852,13 +37292,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_bilinear2d_out -torch_upsample_bilinear2d_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch_upsample_bilinear2d_out <- function(out, self, output_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bilinear2d_out', @@ -36892,13 +37330,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_linear1d_backward -torch_upsample_linear1d_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales")) +torch_upsample_linear1d_backward <- function(grad_output, output_size, input_size, align_corners, scales = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_linear1d_backward', @@ -36912,14 +37349,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_linear1d_backward_out -torch_upsample_linear1d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch_upsample_linear1d_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_linear1d_backward_out', @@ -36933,13 +37368,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_linear1d_out -torch_upsample_linear1d_out <- function(out, input, self, output_size, align_corners, scale_factors, scales = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch_upsample_linear1d_out <- function(out, self, output_size, align_corners, scales = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_linear1d_out', @@ -36971,12 +37404,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest1d_backward -torch_upsample_nearest1d_backward <- function(grad_output, output_size, input_size, scale_factors, scales = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales")) +torch_upsample_nearest1d_backward <- function(grad_output, output_size, input_size, scales = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest1d_backward', @@ -36990,13 +37422,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest1d_backward_out -torch_upsample_nearest1d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch_upsample_nearest1d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest1d_backward_out', @@ -37010,11 +37440,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest1d_out -torch_upsample_nearest1d_out <- function(out, input, self, output_size, scale_factors, scales = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch_upsample_nearest1d_out <- function(out, self, output_size, scales = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest1d_out', @@ -37047,13 +37477,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest2d_backward -torch_upsample_nearest2d_backward <- function(grad_output, output_size, input_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales_h", "scales_w")) +torch_upsample_nearest2d_backward <- function(grad_output, output_size, input_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest2d_backward', @@ -37067,14 +37495,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest2d_backward_out -torch_upsample_nearest2d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch_upsample_nearest2d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales_h = "double", scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest2d_backward_out', @@ -37088,12 +37513,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest2d_out -torch_upsample_nearest2d_out <- function(out, input, self, output_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch_upsample_nearest2d_out <- function(out, self, output_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest2d_out', @@ -37126,13 +37550,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest3d_backward -torch_upsample_nearest3d_backward <- function(grad_output, output_size, input_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales_d", "scales_h", "scales_w")) +torch_upsample_nearest3d_backward <- function(grad_output, output_size, input_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales_d", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales_d = "double", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest3d_backward', @@ -37146,14 +37568,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest3d_backward_out -torch_upsample_nearest3d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch_upsample_nearest3d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales_d", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales_d = "double", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest3d_backward_out', @@ -37167,12 +37587,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest3d_out -torch_upsample_nearest3d_out <- function(out, input, self, output_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch_upsample_nearest3d_out <- function(out, self, output_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales_d", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales_d = "double", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest3d_out', @@ -37206,13 +37625,13 @@ fun_type = 'namespace' #' @rdname torch_upsample_trilinear3d_backward -torch_upsample_trilinear3d_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_d", "scales_h", "scales_w")) +torch_upsample_trilinear3d_backward <- function(grad_output, output_size, input_size, align_corners, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_d", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_d = "double", scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_d = "double", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_trilinear3d_backward', @@ -37226,14 +37645,13 @@ fun_type = 'namespace' #' @rdname torch_upsample_trilinear3d_backward_out -torch_upsample_trilinear3d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_d = "double", scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch_upsample_trilinear3d_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_d", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_d = "double", + scales_h = "double", scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_trilinear3d_backward_out', @@ -37247,13 +37665,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_trilinear3d_out -torch_upsample_trilinear3d_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_d = "double", scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch_upsample_trilinear3d_out <- function(out, self, output_size, align_corners, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_d", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_d = "double", scales_h = "double", + scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_trilinear3d_out', @@ -37336,11 +37753,11 @@ fun_type = 'namespace' #' @rdname torch_var -torch_var <- function(self, dim, correction, unbiased = TRUE, keepdim = FALSE) { +torch_var <- function(self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") +nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'var', @@ -37354,11 +37771,11 @@ fun_type = 'namespace' #' @rdname torch_var_mean -torch_var_mean <- function(self, dim, correction, unbiased = TRUE, keepdim = FALSE) { +torch_var_mean <- function(self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") +nd_args <- c("self", "dim") return_types <- list(list("Tensor", "Tensor")) call_c_function( fun_name = 'var_mean', @@ -37372,11 +37789,11 @@ fun_type = 'namespace' #' @rdname torch_var_mean_out -torch_var_mean_out <- function(out0, out1, self, dim, correction, keepdim = FALSE) { +torch_var_mean_out <- function(out0, out1, self, dim = NULL, correction = NULL, keepdim = FALSE) { args <- mget(x = c("out0", "out1", "self", "dim", "correction", "keepdim")) expected_types <- list(out0 = "Tensor", out1 = "Tensor", self = "Tensor", dim = "IntArrayRef", correction = "int64_t", keepdim = "bool") -nd_args <- c("out0", "out1", "self", "dim", "correction") +nd_args <- c("out0", "out1", "self") return_types <- list(list("Tensor", "Tensor")) call_c_function( fun_name = 'var_mean_out', @@ -37390,11 +37807,11 @@ fun_type = 'namespace' #' @rdname torch_var_out -torch_var_out <- function(out, self, dim, correction, unbiased = TRUE, keepdim = FALSE) { +torch_var_out <- function(out, self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("out", "self", "dim", "correction", "unbiased", "keepdim")) expected_types <- list(out = "Tensor", self = "Tensor", dim = c("IntArrayRef", "DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("out", "self", "dim", "correction") +nd_args <- c("out", "self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'var_out', diff --git a/R/install.R b/R/install.R index 60a022ac3e..76f5ae873a 100644 --- a/R/install.R +++ b/R/install.R @@ -1,5 +1,5 @@ branch <- "main" -torch_version <- "1.13.1" +torch_version <- "2.0.1" #' Install Torch #' diff --git a/inst/include/lantern/lantern.h b/inst/include/lantern/lantern.h index 7a3706a453..4224b2ee4a 100644 --- a/inst/include/lantern/lantern.h +++ b/inst/include/lantern/lantern.h @@ -2865,6 +2865,16 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_affine_grid_generator_tensor_intarrayref_bool(void* theta, void* size, void* align_corners) { LANTERN_CHECK_LOADED void* ret = _lantern_affine_grid_generator_tensor_intarrayref_bool(theta, size, align_corners); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_affine_grid_generator_backward_tensor_intarrayref_bool)(void* grad, void* size, void* align_corners); HOST_API void* lantern_affine_grid_generator_backward_tensor_intarrayref_bool(void* grad, void* size, void* align_corners) { LANTERN_CHECK_LOADED void* ret = _lantern_affine_grid_generator_backward_tensor_intarrayref_bool(grad, size, align_corners); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__is_all_true_tensor)(void* self); + HOST_API void* lantern__is_all_true_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__is_all_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor__is_all_true_tensor)(void* self); + HOST_API void* lantern_Tensor__is_all_true_tensor(void* self) { void* ret = _lantern_Tensor__is_all_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__is_any_true_tensor)(void* self); + HOST_API void* lantern__is_any_true_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__is_any_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor__is_any_true_tensor)(void* self); + HOST_API void* lantern_Tensor__is_any_true_tensor(void* self) { void* ret = _lantern_Tensor__is_any_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__test_check_tensor_tensor)(void* self); + HOST_API void* lantern__test_check_tensor_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__test_check_tensor_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_all_tensor_intt_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_all_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_all_tensor_intt_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_all_tensor_intt_bool)(void* self, void* dim, void* keepdim); @@ -4279,10 +4289,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); + HOST_API void* lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* output, void* input, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); @@ -4375,6 +4383,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(void* self, void* grad_output, void* weight, void* padding, void* stride, void* dilation, void* groups, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(self, grad_output, weight, padding, stride, dilation, groups, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(self, weight, bias, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool)(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train); + HOST_API void* lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor)(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace); + HOST_API void* lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon); HOST_API void* lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double)(void* input, void* grad_output, void* weight, void* running_mean, void* running_var, void* save_mean, void* save_var, void* epsilon); @@ -4401,10 +4413,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mm_out_tensor_tensor_tensor(void* out, void* self, void* mat2) { LANTERN_CHECK_LOADED void* ret = _lantern_mm_out_tensor_tensor_tensor(out, self, mat2); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_tensor_tensor)(void* sparse, void* dense); HOST_API void* lantern__sparse_mm_tensor_tensor(void* sparse, void* dense) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_tensor_tensor(sparse, dense); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_tensor_tensor_cstringview)(void* sparse, void* dense, void* reduce); + HOST_API void* lantern__sparse_mm_tensor_tensor_cstringview(void* sparse, void* dense, void* reduce) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_tensor_tensor_cstringview(sparse, dense, reduce); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_sparse_matmul_tensor_tensor)(void* self, void* other); HOST_API void* lantern__sparse_sparse_matmul_tensor_tensor(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_sparse_matmul_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_mask_helper_tensor_tensor)(void* t, void* mask_indices); - HOST_API void* lantern__sparse_mask_helper_tensor_tensor(void* t, void* mask_indices) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mask_helper_tensor_tensor(t, mask_indices); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mode_tensor_intt_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_mode_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_mode_tensor_intt_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_mode_tensor_intt_bool)(void* self, void* dim, void* keepdim); @@ -4477,6 +4489,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); HOST_API void* lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(input, weight, bias, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_stats_tensor_double)(void* input, void* eps); HOST_API void* lantern_batch_norm_stats_tensor_double(void* input, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_batch_norm_stats_tensor_double(input, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_elemt_tensor_tensor_tensor_tensor_tensor_double)(void* input, void* weight, void* bias, void* mean, void* invstd, void* eps); @@ -4715,6 +4735,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_reshape_tensor_intarrayref(void* self, void* shape) { LANTERN_CHECK_LOADED void* ret = _lantern_reshape_tensor_intarrayref(self, shape); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_reshape_tensor_intarrayref)(void* self, void* shape); HOST_API void* lantern_Tensor_reshape_tensor_intarrayref(void* self, void* shape) { void* ret = _lantern_Tensor_reshape_tensor_intarrayref(self, shape); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__reshape_copy_tensor_intarrayref)(void* self, void* size); + HOST_API void* lantern__reshape_copy_tensor_intarrayref(void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_copy_tensor_intarrayref(self, size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_tensor_intarrayref_intarrayref)(void* self, void* size, void* stride); HOST_API void* lantern__reshape_alias_tensor_intarrayref_intarrayref(void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_tensor_intarrayref_intarrayref(self, size, stride); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor__reshape_alias_tensor_intarrayref_intarrayref)(void* self, void* size, void* stride); @@ -4763,10 +4785,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_prelu_tensor_tensor(void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_prelu_tensor_tensor)(void* self, void* weight); HOST_API void* lantern_Tensor_prelu_tensor_tensor(void* self, void* weight) { void* ret = _lantern_Tensor_prelu_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); - HOST_API void* lantern_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_prelu_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); - HOST_API void* lantern_Tensor_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { void* ret = _lantern_Tensor_prelu_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__prelu_kernel_tensor_tensor)(void* self, void* weight); + HOST_API void* lantern__prelu_kernel_tensor_tensor(void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__prelu_kernel_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__prelu_kernel_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); + HOST_API void* lantern__prelu_kernel_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__prelu_kernel_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_gelu_out_tensor_tensor_cstringview)(void* out, void* self, void* approximate); HOST_API void* lantern_gelu_out_tensor_tensor_cstringview(void* out, void* self, void* approximate) { LANTERN_CHECK_LOADED void* ret = _lantern_gelu_out_tensor_tensor_cstringview(out, self, approximate); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_gelu__tensor_cstringview)(void* self, void* approximate); @@ -5003,10 +5025,16 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_squeeze_tensor_dimname(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze_tensor_dimname)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze_tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_squeeze_tensor_intarrayref(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_Tensor_squeeze_tensor_intarrayref(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor)(void* self); HOST_API void* lantern_Tensor_squeeze__tensor(void* self) { void* ret = _lantern_Tensor_squeeze__tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_intt)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze__tensor_intt(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_Tensor_squeeze__tensor_intarrayref(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_dimname)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze__tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); @@ -5361,6 +5389,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_where_tensor_scalar_tensor(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_scalar_tensor(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor_tensor_scalar)(void* condition, void* self, void* other); HOST_API void* lantern_where_tensor_tensor_scalar(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_tensor_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_where_tensor_tensor_scalar)(void* condition, void* self, void* other); + HOST_API void* lantern_Tensor_where_tensor_tensor_scalar(void* condition, void* self, void* other) { void* ret = _lantern_Tensor_where_tensor_tensor_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor_scalar_scalar)(void* condition, void* self, void* other); HOST_API void* lantern_where_tensor_scalar_scalar(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_scalar_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor)(void* condition); @@ -5471,8 +5501,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_frexp_tensor(void* self) { void* ret = _lantern_Tensor_frexp_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frexp_out_tensor_tensor_tensor)(void* mantissa, void* exponent, void* self); HOST_API void* lantern_frexp_out_tensor_tensor_tensor(void* mantissa, void* exponent, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_frexp_out_tensor_tensor_tensor(mantissa, exponent, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_tensor)(void* self); - HOST_API void* lantern_frobenius_norm_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_frobenius_norm_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_tensor_intarrayref_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_frobenius_norm_tensor_intarrayref_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_frobenius_norm_tensor_intarrayref_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* dim, void* keepdim); @@ -5551,6 +5579,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out, self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); HOST_API void* lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview)(void* self, void* other, void* reduce); + HOST_API void* lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(void* self, void* other, void* reduce) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(self, other, reduce); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool)(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask); + HOST_API void* lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(self, grad_out, weight, reduce, arg_out, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar)(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha); HOST_API void* lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out, self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_addmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); @@ -5683,20 +5715,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_unbind_tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_unbind_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor_intt)(void* self, void* sparse_dim); HOST_API void* lantern_Tensor_to_sparse_tensor_intt(void* self, void* sparse_dim) { void* ret = _lantern_Tensor_to_sparse_tensor_intt(self, sparse_dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csr_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_csr_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_csr_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csc_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_csc_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_csc_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsr_tensor_intarrayref)(void* self, void* blocksize); - HOST_API void* lantern_Tensor_to_sparse_bsr_tensor_intarrayref(void* self, void* blocksize) { void* ret = _lantern_Tensor_to_sparse_bsr_tensor_intarrayref(self, blocksize); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsc_tensor_intarrayref)(void* self, void* blocksize); - HOST_API void* lantern_Tensor_to_sparse_bsc_tensor_intarrayref(void* self, void* blocksize) { void* ret = _lantern_Tensor_to_sparse_bsc_tensor_intarrayref(self, blocksize); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt)(void* self, void* layout, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(void* self, void* layout, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(self, layout, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csr_tensor_intt)(void* self, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_csr_tensor_intt(void* self, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_csr_tensor_intt(self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csc_tensor_intt)(void* self, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_csc_tensor_intt(void* self, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_csc_tensor_intt(self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt)(void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt)(void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_mkldnn_tensor_scalartype)(void* self, void* dtype); HOST_API void* lantern_Tensor_to_mkldnn_tensor_scalartype(void* self, void* dtype) { void* ret = _lantern_Tensor_to_mkldnn_tensor_scalartype(self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* padding, void* stride, void* dilation, void* groups); - HOST_API void* lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref)(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size); + HOST_API void* lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(self, padding, stride, dilation, groups, input_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_mkldnn_backward_tensor_tensor)(void* grad, void* input); @@ -5821,8 +5853,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__local_scalar_dense_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__local_scalar_dense_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); HOST_API void* lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor)(void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias); HOST_API void* lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor(void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias) { LANTERN_CHECK_LOADED void* ret = _lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor(input_gates, hidden_gates, cx, input_bias, hidden_bias); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_backward_impl_tensor_tensor_tensor_tensor_tensor_bool)(void* grad_hy, void* grad_cy, void* cx, void* cy, void* workspace, void* has_bias); @@ -6223,8 +6255,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_diag_tensor_intt(void* self, void* diagonal) { LANTERN_CHECK_LOADED void* ret = _lantern_diag_tensor_intt(self, diagonal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_diag_tensor_intt)(void* self, void* diagonal); HOST_API void* lantern_Tensor_diag_tensor_intt(void* self, void* diagonal) { void* ret = _lantern_Tensor_diag_tensor_intt(self, diagonal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_diag_backward_tensor_intarrayref_intt)(void* grad, void* input_sizes, void* diagonal); - HOST_API void* lantern_diag_backward_tensor_intarrayref_intt(void* grad, void* input_sizes, void* diagonal) { LANTERN_CHECK_LOADED void* ret = _lantern_diag_backward_tensor_intarrayref_intt(grad, input_sizes, diagonal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_cross_out_tensor_tensor_tensor_intt)(void* out, void* self, void* other, void* dim); HOST_API void* lantern_cross_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_cross_out_tensor_tensor_tensor_intt(out, self, other, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_cross_tensor_tensor_intt)(void* self, void* other, void* dim); @@ -6521,14 +6551,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool(void* self, void* B, void* upper, void* left, void* unitriangular) { LANTERN_CHECK_LOADED void* ret = _lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool(self, B, upper, left, unitriangular); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_linalg_vander_tensor_intt)(void* x, void* N); HOST_API void* lantern_linalg_vander_tensor_intt(void* x, void* N) { LANTERN_CHECK_LOADED void* ret = _lantern_linalg_vander_tensor_intt(x, N); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_symeig_out_tensor_tensor_tensor_bool_bool)(void* e, void* V, void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_symeig_out_tensor_tensor_tensor_bool_bool(void* e, void* V, void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern_symeig_out_tensor_tensor_tensor_bool_bool(e, V, self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_symeig_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern_symeig_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_symeig_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_Tensor_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { void* ret = _lantern_Tensor_symeig_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__symeig_helper_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern__symeig_helper_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__symeig_helper_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool)(void* U, void* S, void* V, void* self, void* some, void* compute_uv); HOST_API void* lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(void* U, void* S, void* V, void* self, void* some, void* compute_uv) { LANTERN_CHECK_LOADED void* ret = _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(U, S, V, self, some, compute_uv); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_svd_tensor_bool_bool)(void* self, void* some, void* compute_uv); @@ -6819,6 +6841,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_max_tensor_tensor(void* self, void* other) { void* ret = _lantern_Tensor_max_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_max_out_tensor_tensor_tensor)(void* out, void* self, void* other); HOST_API void* lantern_max_out_tensor_tensor_tensor(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_max_out_tensor_tensor_tensor(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_max_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_max_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_minimum_tensor_tensor)(void* self, void* other); HOST_API void* lantern_minimum_tensor_tensor(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_minimum_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_minimum_tensor_tensor)(void* self, void* other); @@ -7007,6 +7031,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div__tensorlist_scalar)(void* self, void* scalar); HOST_API void* lantern__foreach_div__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_maximum_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_maximum__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_minimum_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_minimum__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_tensorlist_tensorlist_scalar)(void* self, void* other, void* alpha); HOST_API void* lantern__foreach_add_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_tensorlist_tensorlist_scalar(self, other, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add__tensorlist_tensorlist_scalar)(void* self, void* other, void* alpha); @@ -7023,6 +7063,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div__tensorlist_tensorlist)(void* self, void* other); HOST_API void* lantern__foreach_div__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_min_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_min__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_max_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_max__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_tensorlist_arrayrefscalar)(void* self, void* scalars); HOST_API void* lantern__foreach_add_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add__tensorlist_arrayrefscalar)(void* self, void* scalars); @@ -7039,6 +7095,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_mul__tensorlist_arrayrefscalar)(void* self, void* scalars); HOST_API void* lantern__foreach_mul__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_maximum_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_maximum__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_minimum_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_minimum__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_exp_tensorlist)(void* self); HOST_API void* lantern__foreach_exp_tensorlist(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_exp_tensorlist(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_zero__tensorlist)(void* self); @@ -7159,26 +7231,34 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar)(void* self, void* tensor1, void* tensor2, void* value); HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar)(void* self, void* tensor1, void* tensor2, void* value); HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_norm_tensorlist_scalar)(void* self, void* ord); HOST_API void* lantern__foreach_norm_tensorlist_scalar(void* self, void* ord) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_norm_tensorlist_scalar(self, ord); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist)(void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist)(void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_tensorlist_tensorlist_scalar)(void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp_tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_tensorlist_tensorlist_scalar(self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp__tensorlist_tensorlist_scalar)(void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp__tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp__tensorlist_tensorlist_scalar(self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_tensor_tensor_bool_bool)(void* self, void* boundaries, void* out_int32, void* right); HOST_API void* lantern_bucketize_tensor_tensor_bool_bool(void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_tensor_tensor_bool_bool(self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_out_tensor_tensor_tensor_bool_bool)(void* out, void* self, void* boundaries, void* out_int32, void* right); @@ -7187,8 +7267,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_bucketize_scalar_tensor_bool_bool(void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_scalar_tensor_bool_bool(self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor)(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__torch_cuda_cu_linker_symbol_op_tensor)(void* self); - HOST_API void* lantern__torch_cuda_cu_linker_symbol_op_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__torch_cuda_cu_linker_symbol_op_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor)(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(out, sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_tensor_scalar_bool_bool_cstringview_tensor)(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); @@ -7529,52 +7607,28 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_pad_tensor_intarrayref_cstringview_double(void* self, void* pad, void* mode, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern_pad_tensor_intarrayref_cstringview_double(self, pad, mode, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double)(void* out, void* self, void* output_size, void* align_corners, void* scales); HOST_API void* lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(void* out, void* self, void* output_size, void* align_corners, void* scales) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(out, self, output_size, align_corners, scales); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_tensor_intarrayref_bool_double)(void* self, void* output_size, void* align_corners, void* scales); @@ -8309,6 +8363,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_squeeze_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_tensor_intt)(void* self, void* dim); HOST_API void* lantern_squeeze_copy_tensor_intt(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_squeeze_copy_tensor_intarrayref(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_t_copy_tensor)(void* self); HOST_API void* lantern_t_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_tensor_intt_intt)(void* self, void* dim0, void* dim1); @@ -8333,6 +8389,12 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_row_indices_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_row_indices_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_tensor_intt)(void* self, void* dim); HOST_API void* lantern_unbind_copy_tensor_intt(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_out_tensorlist_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_out_tensorlist_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_split_copy_out_tensorlist_tensor_intt_intt)(void* out, void* self, void* split_size, void* dim); + HOST_API void* lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_copy_out_tensorlist_tensor_intt_intt(out, self, split_size, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt)(void* out, void* self, void* split_sizes, void* dim); + HOST_API void* lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out, self, split_sizes, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_view_copy_tensor_intarrayref)(void* self, void* size); HOST_API void* lantern_view_copy_tensor_intarrayref(void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_tensor_intarrayref(self, size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_view_copy_tensor_scalartype)(void* self, void* dtype); @@ -8341,88 +8403,40 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_unfold_copy_tensor_intt_intt_intt(void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_tensor_intt_intt_intt(self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_tensor)(void* self); HOST_API void* lantern_alias_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__fw_primal_copy_out_tensor_tensor_intt)(void* out, void* self, void* level); - HOST_API void* lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__fw_primal_copy_out_tensor_tensor_intt(out, self, level); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__make_dual_copy_out_tensor_tensor_tensor_intt)(void* out, void* primal, void* tangent, void* level); - HOST_API void* lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out, primal, tangent, level); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_as_real_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_real_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_as_complex_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_complex_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__conj_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__conj_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__neg_view_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__neg_view_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt)(void* out, void* self, void* size, void* stride, void* storage_offset); - HOST_API void* lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_CHECK_LOADED void* ret = _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out, self, size, stride, storage_offset); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); - HOST_API void* lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); - HOST_API void* lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_CHECK_LOADED void* ret = _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out, self, offset, dim1, dim2); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_expand_copy_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* size, void* implicit); - HOST_API void* lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_CHECK_LOADED void* ret = _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out, self, size, implicit); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_permute_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dims); - HOST_API void* lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_CHECK_LOADED void* ret = _lantern_permute_copy_out_tensor_tensor_intarrayref(out, self, dims); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref)(void* out, void* self, void* size, void* stride); - HOST_API void* lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out, self, size, stride); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_select_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim, void* index); - HOST_API void* lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_copy_out_tensor_tensor_intt_intt(out, self, dim, index); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_detach_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_detach_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt)(void* out, void* self, void* dim, void* start, void* end, void* step); - HOST_API void* lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out, self, dim, start, end, step); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_split_copy_out_tensorlist_tensor_intt_intt)(void* out, void* self, void* split_size, void* dim); - HOST_API void* lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_copy_out_tensorlist_tensor_intt_intt(out, self, split_size, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt)(void* out, void* self, void* split_sizes, void* dim); - HOST_API void* lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out, self, split_sizes, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_t_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim0, void* dim1); - HOST_API void* lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_CHECK_LOADED void* ret = _lantern_transpose_copy_out_tensor_tensor_intt_intt(out, self, dim0, dim1); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unsqueeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unsqueeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__values_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_values_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_crow_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_crow_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_col_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_col_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_out_tensorlist_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_out_tensorlist_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); - HOST_API void* lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); - HOST_API void* lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* dimension, void* size, void* step); - HOST_API void* lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out, self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_alias_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref)(void* self, void* padding, void* output_size); HOST_API void* lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(void* self, void* padding, void* output_size) { void* ret = _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(self, padding, output_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_softmax_with_shape_tensor_tensor)(void* self, void* query); HOST_API void* lantern__nested_tensor_softmax_with_shape_tensor_tensor(void* self, void* query) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_softmax_with_shape_tensor_tensor(self, query); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double)(void* self, void* weight, void* bias, void* eps); - HOST_API void* lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(void* self, void* weight, void* bias, void* eps) { void* ret = _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(self, weight, bias, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt)(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type); HOST_API void* lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type); HOST_API void* lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal); + HOST_API void* lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(query, key, value, attn_mask, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); HOST_API void* lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); - HOST_API void* lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); - HOST_API void* lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal); + HOST_API void* lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(query, key, value, attn_mask, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask); + HOST_API void* lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask); + HOST_API void* lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(query, key, value, dropout_p, is_causal, return_debug_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt)(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset); + HOST_API void* lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool)(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal); + HOST_API void* lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(query, key, value, compute_log_sumexp, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs); + HOST_API void* lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool)(void* query, void* key, void* value, void* is_causal); + HOST_API void* lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(void* query, void* key, void* value, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(query, key, value, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool)(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask); + HOST_API void* lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt)(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset); + HOST_API void* lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool)(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal); + HOST_API void* lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal) { LANTERN_CHECK_LOADED void* ret = _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs); + HOST_API void* lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_CHECK_LOADED void* ret = _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double)(void* q, void* k, void* v, void* dropout_p); HOST_API void* lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(void* q, void* k, void* v, void* dropout_p) { LANTERN_CHECK_LOADED void* ret = _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(q, k, v, dropout_p); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask); @@ -8431,8 +8445,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_special_airy_ai_tensor(void* x) { LANTERN_CHECK_LOADED void* ret = _lantern_special_airy_ai_tensor(x); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_special_airy_ai_out_tensor_tensor)(void* out, void* x); HOST_API void* lantern_special_airy_ai_out_tensor_tensor(void* out, void* x) { LANTERN_CHECK_LOADED void* ret = _lantern_special_airy_ai_out_tensor_tensor(out, x); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool)(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal); - HOST_API void* lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor)(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value); HOST_API void* lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, incr_key, incr_value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* incr_key, void* incr_value, void* need_weights, void* average_attn_weights); @@ -8629,6 +8641,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foobar_tensor_bool_bool_bool(void* self, void* arg1, void* arg2, void* arg3) { LANTERN_CHECK_LOADED void* ret = _lantern__foobar_tensor_bool_bool_bool(self, arg1, arg2, arg3); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); HOST_API void* lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt)(void* out, void* self, void* other, void* self_num_batch_dims); HOST_API void* lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* self_num_batch_dims) { LANTERN_CHECK_LOADED void* ret = _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(out, self, other, self_num_batch_dims); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__cudnn_ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* deterministic, void* zero_infinity); @@ -8729,6 +8743,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* self, void* grid, void* grad_output) { LANTERN_CHECK_LOADED void* ret = _lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor(out0, out1, self, grid, grad_output); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity); HOST_API void* lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity); + HOST_API void* lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool)(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity); HOST_API void* lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(out, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_diag_embed_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); @@ -8855,10 +8871,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__aminmax_out_tensor_tensor_tensor(void* out0, void* out1, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__aminmax_out_tensor_tensor_tensor(out0, out1, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__aminmax_out_tensor_tensor_tensor_intt_bool)(void* out0, void* out1, void* self, void* dim, void* keepdim); HOST_API void* lantern__aminmax_out_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern__aminmax_out_tensor_tensor_tensor_intt_bool(out0, out1, self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); + HOST_API void* lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* output, void* input, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); @@ -8881,6 +8895,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(void* out0, void* out1, void* out2, void* self, void* grad_output, void* weight, void* padding, void* stride, void* dilation, void* groups, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(out0, out1, out2, self, grad_output, weight, padding, stride, dilation, groups, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, weight, bias, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train); + HOST_API void* lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor)(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace); + HOST_API void* lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon); HOST_API void* lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out0, out1, out2, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double)(void* out0, void* out1, void* out2, void* input, void* grad_output, void* weight, void* running_mean, void* running_var, void* save_mean, void* save_var, void* epsilon); @@ -8897,10 +8915,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight, void* weight_stride0, void* weight_buf, void* hx, void* cx, void* output, void* grad_output, void* grad_hy, void* grad_cy, void* mode, void* hidden_size, void* num_layers, void* batch_first, void* dropout, void* train, void* bidirectional, void* batch_sizes, void* dropout_state, void* reserve, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool(out0, out1, out2, out3, input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor)(void* out, void* self, void* other); HOST_API void* lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(out, self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_mask_helper_out_tensor_tensor_tensor)(void* out, void* t, void* mask_indices); - HOST_API void* lantern__sparse_mask_helper_out_tensor_tensor_tensor(void* out, void* t, void* mask_indices) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mask_helper_out_tensor_tensor_tensor(out, t, mask_indices); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mul_out_tensor_tensor_scalar)(void* out, void* self, void* other); HOST_API void* lantern_mul_out_tensor_tensor_scalar(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_mul_out_tensor_tensor_scalar(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_stats_out_tensor_tensor_tensor_double)(void* out0, void* out1, void* input, void* eps); HOST_API void* lantern_batch_norm_stats_out_tensor_tensor_tensor_double(void* out0, void* out1, void* input, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_batch_norm_stats_out_tensor_tensor_tensor_double(out0, out1, input, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_gather_stats_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_intt)(void* out0, void* out1, void* input, void* mean, void* invstd, void* running_mean, void* running_var, void* momentum, void* eps, void* count); @@ -8965,10 +8983,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__mkldnn_reshape_out_tensor_tensor_intarrayref(void* out, void* self, void* shape) { LANTERN_CHECK_LOADED void* ret = _lantern__mkldnn_reshape_out_tensor_tensor_intarrayref(out, self, shape); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_relu_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_relu_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_relu_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_out_tensor_tensor_tensor)(void* out, void* self, void* weight); - HOST_API void* lantern_prelu_out_tensor_tensor_tensor(void* out, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_out_tensor_tensor_tensor(out, self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor)(void* out0, void* out1, void* grad_output, void* self, void* weight); - HOST_API void* lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(out0, out1, grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt)(void* out, void* grad_output, void* input_sizes, void* dim, void* index); HOST_API void* lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(void* out, void* grad_output, void* input_sizes, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(out, grad_output, input_sizes, dim, index); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_celu_out_tensor_tensor_scalar)(void* out, void* self, void* alpha); @@ -9131,20 +9145,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_copy_sparse_to_sparse_tensor_tensor_bool(void* self, void* src, void* non_blocking) { LANTERN_CHECK_LOADED void* ret = _lantern_copy_sparse_to_sparse_tensor_tensor_bool(self, src, non_blocking); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor_intt)(void* out, void* self, void* sparse_dim); HOST_API void* lantern_to_sparse_out_tensor_tensor_intt(void* out, void* self, void* sparse_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor_intt(out, self, sparse_dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csr_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_csr_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csr_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csc_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_csc_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csc_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref)(void* out, void* self, void* blocksize); - HOST_API void* lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(out, self, blocksize); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref)(void* out, void* self, void* blocksize); - HOST_API void* lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(out, self, blocksize); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt)(void* out, void* self, void* layout, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(void* out, void* self, void* layout, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(out, self, layout, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csr_out_tensor_tensor_intt)(void* out, void* self, void* dense_dim); + HOST_API void* lantern_to_sparse_csr_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csr_out_tensor_tensor_intt(out, self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csc_out_tensor_tensor_intt)(void* out, void* self, void* dense_dim); + HOST_API void* lantern_to_sparse_csc_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csc_out_tensor_tensor_intt(out, self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt)(void* out, void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(out, self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt)(void* out, void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(out, self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_mkldnn_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); HOST_API void* lantern_to_mkldnn_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_to_mkldnn_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups); - HOST_API void* lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size); + HOST_API void* lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(out, self, padding, stride, dilation, groups, input_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_quantize_per_tensor_dynamic_out_tensor_tensor_scalartype_bool)(void* out, void* self, void* dtype, void* reduce_range); @@ -9187,10 +9201,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool(void* self, void* observer_on, void* fake_quant_on, void* running_min, void* running_max, void* scale, void* zero_point, void* averaging_const, void* quant_min, void* quant_max, void* ch_axis, void* per_row_fake_quant, void* symmetric_quant) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__to_copy_out_tensor_tensor_bool_memoryformat)(void* out, void* self, void* non_blocking, void* memory_format); HOST_API void* lantern__to_copy_out_tensor_tensor_bool_memoryformat(void* out, void* self, void* non_blocking, void* memory_format) { LANTERN_CHECK_LOADED void* ret = _lantern__to_copy_out_tensor_tensor_bool_memoryformat(out, self, non_blocking, memory_format); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor)(void* out0, void* out1, void* out2, void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias); HOST_API void* lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* out2, void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias) { LANTERN_CHECK_LOADED void* ret = _lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(out0, out1, out2, input_gates, hidden_gates, cx, input_bias, hidden_bias); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_backward_impl_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool)(void* out0, void* out1, void* out2, void* grad_hy, void* grad_cy, void* cx, void* cy, void* workspace, void* has_bias); @@ -9293,8 +9307,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_triu_indices_out_tensor_intt_intt_intt(void* out, void* row, void* col, void* offset) { LANTERN_CHECK_LOADED void* ret = _lantern_triu_indices_out_tensor_intt_intt_intt(out, row, col, offset); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_trace_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_trace_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_trace_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool)(void* out0, void* out1, void* self, void* eigenvectors, void* upper); - HOST_API void* lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(void* out0, void* out1, void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(out0, out1, self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool)(void* out, void* self, void* A, void* upper); HOST_API void* lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(void* out, void* self, void* A, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(out, self, A, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_dist_out_tensor_tensor_tensor_scalar)(void* out, void* self, void* other, void* p); @@ -9329,6 +9341,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* other, void* alpha); HOST_API void* lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(out, self, other, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* other, void* alpha); @@ -9337,6 +9357,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); HOST_API void* lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_sub_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); @@ -9345,6 +9373,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_exp_out_tensorlist_tensorlist)(void* out, void* self); HOST_API void* lantern__foreach_exp_out_tensorlist_tensorlist(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_exp_out_tensorlist_tensorlist(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_zero_out_tensorlist_tensorlist)(void* out, void* self); @@ -9411,18 +9447,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar(out, self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); - HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); - HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_norm_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* ord); HOST_API void* lantern__foreach_norm_out_tensorlist_tensorlist_scalar(void* out, void* self, void* ord) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_norm_out_tensorlist_tensorlist_scalar(out, self, ord); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(void* out, void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(out, self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(out, self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_out_tensor_scalar_tensor_bool_bool)(void* out, void* self, void* boundaries, void* out_int32, void* right); HOST_API void* lantern_bucketize_out_tensor_scalar_tensor_bool_bool(void* out, void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_out_tensor_scalar_tensor_bool_bool(out, self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor)(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor(out, sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_glu_jvp_out_tensor_tensor_tensor_tensor_intt)(void* out, void* glu, void* x, void* dx, void* dim); @@ -9443,54 +9481,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref(void* out, void* self, void* output_size) { LANTERN_CHECK_LOADED void* ret = _lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref(out, self, output_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor)(void* out, void* grad_output, void* self); HOST_API void* lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(void* out, void* grad_output, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(out, grad_output, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool)(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask); HOST_API void* lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref)(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation); @@ -9521,14 +9511,74 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(void* out, void* grad, void* output, void* data, void* reduce, void* lengths, void* offsets, void* axis, void* initial) { LANTERN_CHECK_LOADED void* ret = _lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(out, grad, output, data, reduce, lengths, offsets, axis, initial); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool)(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory); HOST_API void* lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(out, list, dtype, layout, device, pin_memory); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fw_primal_copy_out_tensor_tensor_intt)(void* out, void* self, void* level); + HOST_API void* lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__fw_primal_copy_out_tensor_tensor_intt(out, self, level); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__make_dual_copy_out_tensor_tensor_tensor_intt)(void* out, void* primal, void* tangent, void* level); + HOST_API void* lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out, primal, tangent, level); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_as_real_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_real_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_as_complex_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_complex_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__conj_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__conj_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__neg_view_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__neg_view_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt)(void* out, void* self, void* size, void* stride, void* storage_offset); + HOST_API void* lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_CHECK_LOADED void* ret = _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out, self, size, stride, storage_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); + HOST_API void* lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); + HOST_API void* lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_CHECK_LOADED void* ret = _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out, self, offset, dim1, dim2); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_expand_copy_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* size, void* implicit); + HOST_API void* lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_CHECK_LOADED void* ret = _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out, self, size, implicit); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_permute_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dims); + HOST_API void* lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_CHECK_LOADED void* ret = _lantern_permute_copy_out_tensor_tensor_intarrayref(out, self, dims); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref)(void* out, void* self, void* size, void* stride); + HOST_API void* lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out, self, size, stride); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_select_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim, void* index); + HOST_API void* lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_copy_out_tensor_tensor_intt_intt(out, self, dim, index); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_detach_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_detach_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt)(void* out, void* self, void* dim, void* start, void* end, void* step); + HOST_API void* lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out, self, dim, start, end, step); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dim); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intarrayref(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_t_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim0, void* dim1); + HOST_API void* lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_CHECK_LOADED void* ret = _lantern_transpose_copy_out_tensor_tensor_intt_intt(out, self, dim0, dim1); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unsqueeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unsqueeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__values_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_values_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_crow_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_crow_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_col_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_col_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_ccol_indices_copy_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_ccol_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_ccol_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_row_indices_copy_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_row_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_row_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); + HOST_API void* lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); + HOST_API void* lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* dimension, void* size, void* step); + HOST_API void* lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out, self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_alias_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref)(void* out, void* self, void* padding, void* output_size); HOST_API void* lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(void* out, void* self, void* padding, void* output_size) { LANTERN_CHECK_LOADED void* ret = _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(out, self, padding, output_size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double)(void* out, void* self, void* weight, void* bias, void* eps); - HOST_API void* lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(void* out, void* self, void* weight, void* bias, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(out, self, weight, bias, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt)(void* out, void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type); HOST_API void* lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* out, void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(out, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_multi_head_attention_out_tensor_tensor_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt)(void* out0, void* out1, void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type); @@ -9547,6 +9597,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); HOST_API void* lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } /* Autogen Headers -- End */ #ifdef __cplusplus @@ -10309,6 +10363,11 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_addr_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_affine_grid_generator_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_affine_grid_generator_backward_tensor_intarrayref_bool) + LOAD_SYMBOL(_lantern__is_all_true_tensor) + LOAD_SYMBOL(_lantern_Tensor__is_all_true_tensor) + LOAD_SYMBOL(_lantern__is_any_true_tensor) + LOAD_SYMBOL(_lantern_Tensor__is_any_true_tensor) + LOAD_SYMBOL(_lantern__test_check_tensor_tensor) LOAD_SYMBOL(_lantern_all_tensor_intt_bool) LOAD_SYMBOL(_lantern_Tensor_all_tensor_intt_bool) LOAD_SYMBOL(_lantern_all_out_tensor_tensor_intt_bool) @@ -11016,8 +11075,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_max_pool1d_with_indices_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) + LOAD_SYMBOL(_lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool3d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) @@ -11064,6 +11122,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__mps_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool) LOAD_SYMBOL(_lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor) LOAD_SYMBOL(_lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_miopen_batch_norm_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_miopen_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_bool_bool) @@ -11077,8 +11137,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_mm_tensor_tensor) LOAD_SYMBOL(_lantern_mm_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__sparse_mm_tensor_tensor) + LOAD_SYMBOL(_lantern__sparse_mm_tensor_tensor_cstringview) LOAD_SYMBOL(_lantern__sparse_sparse_matmul_tensor_tensor) - LOAD_SYMBOL(_lantern__sparse_mask_helper_tensor_tensor) LOAD_SYMBOL(_lantern_mode_tensor_intt_bool) LOAD_SYMBOL(_lantern_Tensor_mode_tensor_intt_bool) LOAD_SYMBOL(_lantern_mode_out_tensor_tensor_tensor_intt_bool) @@ -11115,6 +11175,10 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_narrow_tensor_intt_tensor_intt) LOAD_SYMBOL(_lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_batch_norm_stats_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_elemt_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_elemt_out_tensor_tensor_tensor_tensor_tensor_tensor_double) @@ -11234,6 +11298,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_repeat_interleave_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_reshape_tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_reshape_tensor_intarrayref) + LOAD_SYMBOL(_lantern__reshape_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern__reshape_alias_tensor_intarrayref_intarrayref) LOAD_SYMBOL(_lantern_Tensor__reshape_alias_tensor_intarrayref_intarrayref) LOAD_SYMBOL(_lantern__mkldnn_reshape_tensor_intarrayref) @@ -11258,8 +11323,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_relu6__tensor) LOAD_SYMBOL(_lantern_prelu_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_prelu_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_backward_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_Tensor_prelu_backward_tensor_tensor_tensor) + LOAD_SYMBOL(_lantern__prelu_kernel_tensor_tensor) + LOAD_SYMBOL(_lantern__prelu_kernel_backward_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_gelu_out_tensor_tensor_cstringview) LOAD_SYMBOL(_lantern_gelu__tensor_cstringview) LOAD_SYMBOL(_lantern_gelu_tensor_cstringview) @@ -11378,8 +11443,11 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_intt) LOAD_SYMBOL(_lantern_squeeze_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_dimname) + LOAD_SYMBOL(_lantern_squeeze_tensor_intarrayref) + LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_dimname) LOAD_SYMBOL(_lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_Tensor_sspaddmm_tensor_tensor_tensor_scalar_scalar) @@ -11557,6 +11625,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_where_out_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_where_tensor_scalar_tensor) LOAD_SYMBOL(_lantern_where_tensor_tensor_scalar) + LOAD_SYMBOL(_lantern_Tensor_where_tensor_tensor_scalar) LOAD_SYMBOL(_lantern_where_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_where_tensor) LOAD_SYMBOL(_lantern_norm_except_dim_tensor_intt_intt) @@ -11612,7 +11681,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_frexp_tensor) LOAD_SYMBOL(_lantern_Tensor_frexp_tensor) LOAD_SYMBOL(_lantern_frexp_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_frobenius_norm_tensor) LOAD_SYMBOL(_lantern_frobenius_norm_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_frobenius_norm_out_tensor_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_nuclear_norm_tensor_bool) @@ -11652,6 +11720,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__sparse_addmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar) + LOAD_SYMBOL(_lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview) + LOAD_SYMBOL(_lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool) LOAD_SYMBOL(_lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_addmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_Tensor_addmm_tensor_tensor_tensor_scalar_scalar) @@ -11718,13 +11788,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_unbind_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_unbind_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor_intt) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_csr_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_csc_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsr_tensor_intarrayref) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsc_tensor_intarrayref) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_csr_tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_csc_tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_Tensor_to_mkldnn_tensor_scalartype) - LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref) LOAD_SYMBOL(_lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_to_mkldnn_backward_tensor_tensor) LOAD_SYMBOL(_lantern_quantize_per_tensor_dynamic_tensor_scalartype_bool) @@ -11787,7 +11857,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_promote_types_scalartype_scalartype) LOAD_SYMBOL(_lantern__local_scalar_dense_tensor) LOAD_SYMBOL(_lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) - LOAD_SYMBOL(_lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_impl_tensor_tensor_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_tensor_tensor_tensor_tensor_tensor_bool) @@ -11988,7 +12058,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_diag_out_tensor_tensor_intt) LOAD_SYMBOL(_lantern_diag_tensor_intt) LOAD_SYMBOL(_lantern_Tensor_diag_tensor_intt) - LOAD_SYMBOL(_lantern_diag_backward_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_cross_out_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern_cross_tensor_tensor_intt) LOAD_SYMBOL(_lantern_Tensor_cross_tensor_tensor_intt) @@ -12137,10 +12206,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_linalg_solve_triangular_out_tensor_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern_linalg_vander_tensor_intt) - LOAD_SYMBOL(_lantern_symeig_out_tensor_tensor_tensor_bool_bool) - LOAD_SYMBOL(_lantern_symeig_tensor_bool_bool) - LOAD_SYMBOL(_lantern_Tensor_symeig_tensor_bool_bool) - LOAD_SYMBOL(_lantern__symeig_helper_tensor_bool_bool) LOAD_SYMBOL(_lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_svd_tensor_bool_bool) LOAD_SYMBOL(_lantern_Tensor_svd_tensor_bool_bool) @@ -12286,6 +12351,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_max_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_max_tensor_tensor) LOAD_SYMBOL(_lantern_max_out_tensor_tensor_tensor) + LOAD_SYMBOL(_lantern_max_out_tensor_tensor) LOAD_SYMBOL(_lantern_minimum_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_minimum_tensor_tensor) LOAD_SYMBOL(_lantern_minimum_out_tensor_tensor_tensor) @@ -12380,6 +12446,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add__tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_sub_tensorlist_tensorlist_scalar) @@ -12388,6 +12462,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_add_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_add__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_sub_tensorlist_arrayrefscalar) @@ -12396,6 +12478,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_div__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_exp_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero__tensorlist) LOAD_SYMBOL(_lantern__foreach_exp__tensorlist) @@ -12456,21 +12546,24 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar) - LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_norm_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp__tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp__tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern_bucketize_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_bucketize_out_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_bucketize_scalar_tensor_bool_bool) LOAD_SYMBOL(_lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor) - LOAD_SYMBOL(_lantern__torch_cuda_cu_linker_symbol_op_tensor) LOAD_SYMBOL(_lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern_searchsorted_tensor_scalar_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern__convert_indices_from_coo_to_csr_tensor_intt_bool) @@ -12641,29 +12734,17 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__pad_enum_tensor_intarrayref_intt_double) LOAD_SYMBOL(_lantern_pad_tensor_intarrayref_cstringview_double) LOAD_SYMBOL(_lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double) LOAD_SYMBOL(_lantern_upsample_linear1d_tensor_intarrayref_bool_double) LOAD_SYMBOL(_lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_double) @@ -13031,6 +13112,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_split_with_sizes_copy_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_squeeze_copy_tensor) LOAD_SYMBOL(_lantern_squeeze_copy_tensor_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern_t_copy_tensor) LOAD_SYMBOL(_lantern_transpose_copy_tensor_intt_intt) LOAD_SYMBOL(_lantern_unsqueeze_copy_tensor_intt) @@ -13043,56 +13125,34 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_ccol_indices_copy_tensor) LOAD_SYMBOL(_lantern_row_indices_copy_tensor) LOAD_SYMBOL(_lantern_unbind_copy_tensor_intt) + LOAD_SYMBOL(_lantern_unbind_copy_out_tensorlist_tensor_intt) + LOAD_SYMBOL(_lantern_split_copy_out_tensorlist_tensor_intt_intt) + LOAD_SYMBOL(_lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_view_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern_view_copy_tensor_scalartype) LOAD_SYMBOL(_lantern_unfold_copy_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_alias_copy_tensor) - LOAD_SYMBOL(_lantern__fw_primal_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern__make_dual_copy_out_tensor_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_view_as_real_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_view_as_complex_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__conj_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__neg_view_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt) - LOAD_SYMBOL(_lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt) - LOAD_SYMBOL(_lantern_expand_copy_out_tensor_tensor_intarrayref_bool) - LOAD_SYMBOL(_lantern_permute_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref) - LOAD_SYMBOL(_lantern_select_copy_out_tensor_tensor_intt_intt) - LOAD_SYMBOL(_lantern_detach_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt) - LOAD_SYMBOL(_lantern_split_copy_out_tensorlist_tensor_intt_intt) - LOAD_SYMBOL(_lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt) - LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_t_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_transpose_copy_out_tensor_tensor_intt_intt) - LOAD_SYMBOL(_lantern_unsqueeze_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern__indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__values_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_values_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_crow_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_col_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_unbind_copy_out_tensorlist_tensor_intt) - LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_scalartype) - LOAD_SYMBOL(_lantern_unfold_copy_out_tensor_tensor_intt_intt_intt) - LOAD_SYMBOL(_lantern_alias_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_to_padded_tensor_tensor_double_intarrayref) LOAD_SYMBOL(_lantern__nested_tensor_softmax_with_shape_tensor_tensor) - LOAD_SYMBOL(_lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt) + LOAD_SYMBOL(_lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool) LOAD_SYMBOL(_lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool) - LOAD_SYMBOL(_lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool) - LOAD_SYMBOL(_lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool) + LOAD_SYMBOL(_lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor) + LOAD_SYMBOL(_lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt) + LOAD_SYMBOL(_lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) + LOAD_SYMBOL(_lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool) + LOAD_SYMBOL(_lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool) + LOAD_SYMBOL(_lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt) + LOAD_SYMBOL(_lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool) + LOAD_SYMBOL(_lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_special_airy_ai_tensor) LOAD_SYMBOL(_lantern_special_airy_ai_out_tensor_tensor) - LOAD_SYMBOL(_lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool) LOAD_SYMBOL(_lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_special_bessel_j0_tensor) @@ -13191,6 +13251,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_special_spherical_bessel_j0_out_tensor_tensor) LOAD_SYMBOL(_lantern__foobar_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) LOAD_SYMBOL(_lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__cudnn_ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool_bool) LOAD_SYMBOL(_lantern__cudnn_rnn_flatten_weight_out_tensor_tensorlist_intt_intt_intt_intt_intt_intt_bool_bool) @@ -13241,6 +13302,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_cudnn_grid_sampler_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool) + LOAD_SYMBOL(_lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool) LOAD_SYMBOL(_lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool) LOAD_SYMBOL(_lantern_diag_embed_out_tensor_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_diagonal_backward_out_tensor_tensor_intarrayref_intt_intt_intt) @@ -13304,8 +13366,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_matmul_backward_out_tensor_tensor_tensor_tensor_tensor_stdarraybool) LOAD_SYMBOL(_lantern__aminmax_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__aminmax_out_tensor_tensor_tensor_intt_bool) - LOAD_SYMBOL(_lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) + LOAD_SYMBOL(_lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool3d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) @@ -13317,6 +13378,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__mps_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool) LOAD_SYMBOL(_lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor) LOAD_SYMBOL(_lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_miopen_batch_norm_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_miopen_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_bool_bool) @@ -13325,8 +13388,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_miopen_rnn_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_intt_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor) LOAD_SYMBOL(_lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool) LOAD_SYMBOL(_lantern__sparse_sparse_matmul_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern__sparse_mask_helper_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_mul_out_tensor_tensor_scalar) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_batch_norm_stats_out_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_gather_stats_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_intt) LOAD_SYMBOL(_lantern_batch_norm_gather_stats_with_counts_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_tensor) @@ -13359,8 +13422,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_repeat_interleave_out_tensor_tensor_intt) LOAD_SYMBOL(_lantern__mkldnn_reshape_out_tensor_tensor_intarrayref) LOAD_SYMBOL(_lantern_relu_out_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt) LOAD_SYMBOL(_lantern_celu_out_tensor_tensor_scalar) LOAD_SYMBOL(_lantern_slice_backward_out_tensor_tensor_intarrayref_intt_intt_intt_intt) @@ -13442,13 +13503,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_copy_sparse_to_sparse_out_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern_copy_sparse_to_sparse_tensor_tensor_bool) LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_csr_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_csc_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_bsr_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_to_sparse_bsc_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt) + LOAD_SYMBOL(_lantern_to_sparse_csr_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_to_sparse_csc_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt) + LOAD_SYMBOL(_lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_to_mkldnn_out_tensor_tensor_scalartype) - LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref) LOAD_SYMBOL(_lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_quantize_per_tensor_dynamic_out_tensor_tensor_scalartype_bool) LOAD_SYMBOL(_lantern_quantize_per_tensor_out_tensor_tensor_double_intt_scalartype) @@ -13470,8 +13531,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__fused_moving_avg_obs_fq_helper_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool) LOAD_SYMBOL(_lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool) LOAD_SYMBOL(_lantern__to_copy_out_tensor_tensor_bool_memoryformat) - LOAD_SYMBOL(_lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) - LOAD_SYMBOL(_lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_impl_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern__thnn_fused_gru_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor) @@ -13523,7 +13584,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_tril_indices_out_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_triu_indices_out_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_trace_out_tensor_tensor) - LOAD_SYMBOL(_lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern_dist_out_tensor_tensor_tensor_scalar) LOAD_SYMBOL(_lantern__histogramdd_bin_edges_out_tensorlist_tensor_intarrayref_arrayrefdouble_tensor_bool) @@ -13541,14 +13601,26 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_exp_out_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero_out_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero_tensorlist) @@ -13582,12 +13654,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar) - LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_norm_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern_bucketize_out_tensor_scalar_tensor_bool_bool) - LOAD_SYMBOL(_lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor) LOAD_SYMBOL(_lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern_glu_jvp_out_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern_glu_backward_jvp_out_tensor_tensor_tensor_tensor_tensor_tensor_intt) @@ -13598,30 +13671,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__adaptive_avg_pool2d_backward_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref) LOAD_SYMBOL(_lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool) LOAD_SYMBOL(_lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref) LOAD_SYMBOL(_lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref) @@ -13637,10 +13686,40 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar) LOAD_SYMBOL(_lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar) LOAD_SYMBOL(_lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool) + LOAD_SYMBOL(_lantern__fw_primal_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern__make_dual_copy_out_tensor_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_view_as_real_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_view_as_complex_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__conj_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__neg_view_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt) + LOAD_SYMBOL(_lantern_expand_copy_out_tensor_tensor_intarrayref_bool) + LOAD_SYMBOL(_lantern_permute_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref) + LOAD_SYMBOL(_lantern_select_copy_out_tensor_tensor_intt_intt) + LOAD_SYMBOL(_lantern_detach_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_t_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_transpose_copy_out_tensor_tensor_intt_intt) + LOAD_SYMBOL(_lantern_unsqueeze_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern__indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__values_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_values_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_crow_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_col_indices_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_ccol_indices_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_row_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_scalartype) + LOAD_SYMBOL(_lantern_unfold_copy_out_tensor_tensor_intt_intt_intt) + LOAD_SYMBOL(_lantern_alias_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref) - LOAD_SYMBOL(_lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__native_multi_head_attention_out_tensor_tensor_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt) LOAD_SYMBOL(_lantern__triton_scaled_dot_attention_out_tensor_tensor_tensor_tensor_double) @@ -13650,6 +13729,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foobar_out_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) LOAD_SYMBOL(_lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) /* Autogen Symbols -- End */ return true; diff --git a/man/torch_std.Rd b/man/torch_std.Rd index 795c0b4fda..bb563c9687 100644 --- a/man/torch_std.Rd +++ b/man/torch_std.Rd @@ -5,7 +5,13 @@ \alias{torch_std} \title{Std} \usage{ -torch_std(self, dim, correction, unbiased = TRUE, keepdim = FALSE) +torch_std( + self, + dim = NULL, + correction = NULL, + unbiased = TRUE, + keepdim = FALSE +) } \arguments{ \item{self}{(Tensor) the input tensor.} diff --git a/man/torch_std_mean.Rd b/man/torch_std_mean.Rd index d79a71da2e..39708674da 100644 --- a/man/torch_std_mean.Rd +++ b/man/torch_std_mean.Rd @@ -5,7 +5,13 @@ \alias{torch_std_mean} \title{Std_mean} \usage{ -torch_std_mean(self, dim, correction, unbiased = TRUE, keepdim = FALSE) +torch_std_mean( + self, + dim = NULL, + correction = NULL, + unbiased = TRUE, + keepdim = FALSE +) } \arguments{ \item{self}{(Tensor) the input tensor.} diff --git a/man/torch_symeig.Rd b/man/torch_symeig.Rd index 6be0c5944a..aa222038df 100644 --- a/man/torch_symeig.Rd +++ b/man/torch_symeig.Rd @@ -1,12 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/gen-namespace-docs.R, -% R/gen-namespace-examples.R, R/gen-namespace.R +% R/gen-namespace-examples.R \name{torch_symeig} \alias{torch_symeig} \title{Symeig} -\usage{ -torch_symeig(self, eigenvectors = FALSE, upper = TRUE) -} \arguments{ \item{self}{(Tensor) the input tensor of size \eqn{(*, n, n)} where \code{*} is zero or more batch dimensions consisting of symmetric matrices.} diff --git a/man/torch_var.Rd b/man/torch_var.Rd index 0935891e9b..b9e06d42f1 100644 --- a/man/torch_var.Rd +++ b/man/torch_var.Rd @@ -5,7 +5,13 @@ \alias{torch_var} \title{Var} \usage{ -torch_var(self, dim, correction, unbiased = TRUE, keepdim = FALSE) +torch_var( + self, + dim = NULL, + correction = NULL, + unbiased = TRUE, + keepdim = FALSE +) } \arguments{ \item{self}{(Tensor) the input tensor.} diff --git a/man/torch_var_mean.Rd b/man/torch_var_mean.Rd index 72cfecdf58..facfb6b39f 100644 --- a/man/torch_var_mean.Rd +++ b/man/torch_var_mean.Rd @@ -5,7 +5,13 @@ \alias{torch_var_mean} \title{Var_mean} \usage{ -torch_var_mean(self, dim, correction, unbiased = TRUE, keepdim = FALSE) +torch_var_mean( + self, + dim = NULL, + correction = NULL, + unbiased = TRUE, + keepdim = FALSE +) } \arguments{ \item{self}{(Tensor) the input tensor.} diff --git a/src/RcppExports.cpp b/src/RcppExports.cpp index 32c3bd98ca..87752d320e 100644 --- a/src/RcppExports.cpp +++ b/src/RcppExports.cpp @@ -1522,6 +1522,28 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_method__is_all_true_self_Tensor +XPtrTorchTensor cpp_torch_method__is_all_true_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_method__is_all_true_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method__is_all_true_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_method__is_any_true_self_Tensor +XPtrTorchTensor cpp_torch_method__is_any_true_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_method__is_any_true_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method__is_any_true_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_method_all_self_Tensor_dim_int64_t XPtrTorchTensor cpp_torch_method_all_self_Tensor_dim_int64_t(XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_method_all_self_Tensor_dim_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP keepdimSEXP) { @@ -4988,19 +5010,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor -Rcpp::List cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight); -RcppExport SEXP _torch_cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(grad_output, self, weight)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_hardshrink_self_Tensor XPtrTorchTensor cpp_torch_method_hardshrink_self_Tensor(XPtrTorchTensor self, XPtrTorchScalar lambd); RcppExport SEXP _torch_cpp_torch_method_hardshrink_self_Tensor(SEXP selfSEXP, SEXP lambdSEXP) { @@ -5505,6 +5514,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef(self, dim)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_method_squeeze__self_Tensor XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor(XPtrTorchTensor self); RcppExport SEXP _torch_cpp_torch_method_squeeze__self_Tensor(SEXP selfSEXP) { @@ -5528,6 +5549,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef(self, dim)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_method_squeeze__self_Tensor_dim_Dimname XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_Dimname(XPtrTorchTensor self, XPtrTorchDimname dim); RcppExport SEXP _torch_cpp_torch_method_squeeze__self_Tensor_dim_Dimname(SEXP selfSEXP, SEXP dimSEXP) { @@ -5755,20 +5788,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_std_self_Tensor_dim_DimnameList XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_method_std_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -5783,20 +5802,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_prod_self_Tensor XPtrTorchTensor cpp_torch_method_prod_self_Tensor(XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype); RcppExport SEXP _torch_cpp_torch_method_prod_self_Tensor(SEXP selfSEXP, SEXP dtypeSEXP) { @@ -6153,20 +6158,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_var_self_Tensor_dim_DimnameList XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_method_var_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -6181,20 +6172,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_view_as_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_method_view_as_self_Tensor_other_Tensor(XPtrTorchTensor self, XPtrTorchTensor other); RcppExport SEXP _torch_cpp_torch_method_view_as_self_Tensor_other_Tensor(SEXP selfSEXP, SEXP otherSEXP) { @@ -6220,6 +6197,19 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar +XPtrTorchTensor cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar(XPtrTorchTensor condition, XPtrTorchTensor self, XPtrTorchScalar other); +RcppExport SEXP _torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar(SEXP conditionSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type condition(conditionSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar(condition, self, other)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType XPtrTorchTensor cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType(XPtrTorchTensor self, XPtrTorchoptional_scalar p, XPtrTorchDtype dtype); RcppExport SEXP _torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType(SEXP selfSEXP, SEXP pSEXP, SEXP dtypeSEXP) { @@ -6825,59 +6815,66 @@ BEGIN_RCPP END_RCPP } // cpp_torch_method_to_sparse_self_Tensor -XPtrTorchTensor cpp_torch_method_to_sparse_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_self_Tensor(SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_self_Tensor(XPtrTorchTensor self, XPtrTorchLayout layout, XPtrTorchOptionalIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_self_Tensor(SEXP selfSEXP, SEXP layoutSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_self_Tensor(self)); + Rcpp::traits::input_parameter< XPtrTorchLayout >::type layout(layoutSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type blocksize(blocksizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_self_Tensor(self, layout, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_method_to_sparse_csr_self_Tensor -XPtrTorchTensor cpp_torch_method_to_sparse_csr_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_csr_self_Tensor(SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_csr_self_Tensor(XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_csr_self_Tensor(SEXP selfSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_csr_self_Tensor(self)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_csr_self_Tensor(self, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_method_to_sparse_csc_self_Tensor -XPtrTorchTensor cpp_torch_method_to_sparse_csc_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_csc_self_Tensor(SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_csc_self_Tensor(XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_csc_self_Tensor(SEXP selfSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_csc_self_Tensor(self)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_csc_self_Tensor(self, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef -XPtrTorchTensor cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(SEXP selfSEXP, SEXP blocksizeSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(SEXP selfSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type blocksize(blocksizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(self, blocksize)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(self, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef -XPtrTorchTensor cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(SEXP selfSEXP, SEXP blocksizeSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(SEXP selfSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type blocksize(blocksizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(self, blocksize)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(self, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } @@ -9156,19 +9153,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_symeig_self_Tensor -Rcpp::List cpp_torch_method_symeig_self_Tensor(XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_method_symeig_self_Tensor(SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_symeig_self_Tensor(self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_svd_self_Tensor Rcpp::List cpp_torch_method_svd_self_Tensor(XPtrTorchTensor self, XPtrTorchbool some, XPtrTorchbool compute_uv); RcppExport SEXP _torch_cpp_torch_method_svd_self_Tensor(SEXP selfSEXP, SEXP someSEXP, SEXP compute_uvSEXP) { @@ -10411,20 +10395,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double -XPtrTorchTensor cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double(XPtrTorchTensor self, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchdouble eps); -RcppExport SEXP _torch_cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double(SEXP selfSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP epsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double(self, weight, bias, eps)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__cast_Byte_self_Tensor XPtrTorchTensor cpp_torch_namespace__cast_Byte_self_Tensor(XPtrTorchTensor self, XPtrTorchbool non_blocking); RcppExport SEXP _torch_cpp_torch_namespace__cast_Byte_self_Tensor(SEXP selfSEXP, SEXP non_blockingSEXP) { @@ -11570,6 +11540,39 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__is_all_true_self_Tensor +XPtrTorchTensor cpp_torch_namespace__is_all_true_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__is_all_true_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__is_all_true_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__is_any_true_self_Tensor +XPtrTorchTensor cpp_torch_namespace__is_any_true_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__is_any_true_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__is_any_true_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_check_tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__test_check_tensor_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__test_check_tensor_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_check_tensor_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_all_self_Tensor_dim_int64_t XPtrTorchTensor cpp_torch_namespace_all_self_Tensor_dim_int64_t(XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_all_self_Tensor_dim_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP keepdimSEXP) { @@ -18137,25 +18140,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); -RcppExport SEXP _torch_cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef(SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type ceil_mode(ceil_modeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef(self, kernel_size, stride, padding, dilation, ceil_mode)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); -RcppExport SEXP _torch_cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { +// cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); +RcppExport SEXP _torch_cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -18166,7 +18153,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type ceil_mode(ceil_modeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode)); return rcpp_result_gen; END_RCPP } @@ -18654,6 +18641,65 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(XPtrTorchTensor input, XPtrTorchTensor weight0, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor hx_, XPtrTorchTensor cx_, XPtrTorchbool reverse, XPtrTorchIntArrayRef batch_sizes, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool bidirectional, XPtrTorchbool batch_first, XPtrTorchbool train); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(SEXP inputSEXP, SEXP weight0SEXP, SEXP weight1SEXP, SEXP weight2SEXP, SEXP weight3SEXP, SEXP hx_SEXP, SEXP cx_SEXP, SEXP reverseSEXP, SEXP batch_sizesSEXP, SEXP modeSEXP, SEXP hidden_sizeSEXP, SEXP num_layersSEXP, SEXP has_biasesSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP, SEXP trainSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight0(weight0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight1(weight1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight2(weight2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight3(weight3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hx_(hx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cx_(cx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type reverse(reverseSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type batch_sizes(batch_sizesSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type mode(modeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type hidden_size(hidden_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type num_layers(num_layersSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(XPtrTorchTensor input, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor weight4, XPtrTorchTensor hx_, XPtrTorchTensor cx_tmp, XPtrTorchTensor output, XPtrTorchTensor hy_, XPtrTorchTensor cy_, XPtrTorchOptionalTensor grad_output, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchbool reverse, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchIntArrayRef batch_sizes, XPtrTorchbool batch_first, XPtrTorchTensor workspace); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(SEXP inputSEXP, SEXP weight1SEXP, SEXP weight2SEXP, SEXP weight3SEXP, SEXP weight4SEXP, SEXP hx_SEXP, SEXP cx_tmpSEXP, SEXP outputSEXP, SEXP hy_SEXP, SEXP cy_SEXP, SEXP grad_outputSEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP reverseSEXP, SEXP modeSEXP, SEXP hidden_sizeSEXP, SEXP num_layersSEXP, SEXP has_biasesSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_sizesSEXP, SEXP batch_firstSEXP, SEXP workspaceSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight1(weight1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight2(weight2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight3(weight3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight4(weight4SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hx_(hx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cx_tmp(cx_tmpSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type output(outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hy_(hy_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cy_(cy_SEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_output(grad_outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_hy(grad_hySEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_cy(grad_cySEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type reverse(reverseSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type mode(modeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type hidden_size(hidden_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type num_layers(num_layersSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type batch_sizes(batch_sizesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type workspace(workspaceSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double Rcpp::List cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double(XPtrTorchTensor input, XPtrTorchTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchOptionalTensor running_mean, XPtrTorchOptionalTensor running_var, XPtrTorchbool training, XPtrTorchdouble exponential_average_factor, XPtrTorchdouble epsilon); RcppExport SEXP _torch_cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double(SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP exponential_average_factorSEXP, SEXP epsilonSEXP) { @@ -18876,27 +18922,28 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor -XPtrTorchTensor cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(XPtrTorchTensor self, XPtrTorchTensor other); -RcppExport SEXP _torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view +XPtrTorchTensor cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view(XPtrTorchTensor sparse, XPtrTorchTensor dense, XPtrTorchstring_view reduce); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view(SEXP sparseSEXP, SEXP denseSEXP, SEXP reduceSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type other(otherSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(self, other)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type sparse(sparseSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type dense(denseSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view(sparse, dense, reduce)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor -XPtrTorchTensor cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor(XPtrTorchTensor t, XPtrTorchTensor mask_indices); -RcppExport SEXP _torch_cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor(SEXP tSEXP, SEXP mask_indicesSEXP) { +// cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor +XPtrTorchTensor cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(XPtrTorchTensor self, XPtrTorchTensor other); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(SEXP selfSEXP, SEXP otherSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type t(tSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type mask_indices(mask_indicesSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor(t, mask_indices)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(self, other)); return rcpp_result_gen; END_RCPP } @@ -19176,6 +19223,80 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_mean(running_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_var(running_varSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(input, weight, bias, running_mean, running_var, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor out, XPtrTorchTensor save_mean, XPtrTorchTensor save_invstd, XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(SEXP outSEXP, SEXP save_meanSEXP, SEXP save_invstdSEXP, SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type save_mean(save_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type save_invstd(save_invstdSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_mean(running_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_var(running_varSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(input, weight, bias, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor out, XPtrTorchTensor save_mean, XPtrTorchTensor save_invstd, XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(SEXP outSEXP, SEXP save_meanSEXP, SEXP save_invstdSEXP, SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type save_mean(save_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type save_invstd(save_invstdSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(out, save_mean, save_invstd, input, weight, bias, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double Rcpp::List cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double(XPtrTorchTensor input, XPtrTorchdouble eps); RcppExport SEXP _torch_cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double(SEXP inputSEXP, SEXP epsSEXP) { @@ -20321,6 +20442,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef size); +RcppExport SEXP _torch_cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef(SEXP selfSEXP, SEXP sizeSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef(self, size)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef XPtrTorchTensor cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride); RcppExport SEXP _torch_cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP) { @@ -20503,16 +20636,28 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor -Rcpp::List cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight); -RcppExport SEXP _torch_cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP) { +// cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor +XPtrTorchTensor cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor(XPtrTorchTensor self, XPtrTorchTensor weight); +RcppExport SEXP _torch_cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor(SEXP selfSEXP, SEXP weightSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor(self, weight)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor +Rcpp::List cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight); +RcppExport SEXP _torch_cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(grad_output, self, weight)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor(grad_output, self, weight)); return rcpp_result_gen; END_RCPP } @@ -21473,6 +21618,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef(self, dim)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor XPtrTorchTensor cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor(XPtrTorchTensor self, XPtrTorchTensor mat1, XPtrTorchTensor mat2, XPtrTorchScalar beta, XPtrTorchScalar alpha); RcppExport SEXP _torch_cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor(SEXP selfSEXP, SEXP mat1SEXP, SEXP mat2SEXP, SEXP betaSEXP, SEXP alphaSEXP) { @@ -21894,20 +22051,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_std_mean_self_Tensor Rcpp::List cpp_torch_namespace_std_mean_self_Tensor(XPtrTorchTensor self, XPtrTorchbool unbiased); RcppExport SEXP _torch_cpp_torch_namespace_std_mean_self_Tensor(SEXP selfSEXP, SEXP unbiasedSEXP) { @@ -21934,20 +22077,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t -Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -21962,20 +22091,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t -Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -21991,21 +22106,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(out, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_std_self_Tensor_dim_DimnameList XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -22035,35 +22135,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(out, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_prod_self_Tensor XPtrTorchTensor cpp_torch_namespace_prod_self_Tensor(XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype); RcppExport SEXP _torch_cpp_torch_namespace_prod_self_Tensor(SEXP selfSEXP, SEXP dtypeSEXP) { @@ -22837,20 +22908,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -22866,21 +22923,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(out, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_var_self_Tensor_dim_DimnameList XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -22910,35 +22952,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(out, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_var_mean_self_Tensor Rcpp::List cpp_torch_namespace_var_mean_self_Tensor(XPtrTorchTensor self, XPtrTorchbool unbiased); RcppExport SEXP _torch_cpp_torch_namespace_var_mean_self_Tensor(SEXP selfSEXP, SEXP unbiasedSEXP) { @@ -22965,20 +22978,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t -Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -22993,20 +22992,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t -Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor(XPtrTorchTensor condition, XPtrTorchTensor self, XPtrTorchTensor other); RcppExport SEXP _torch_cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor(SEXP conditionSEXP, SEXP selfSEXP, SEXP otherSEXP) { @@ -23694,17 +23679,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_frobenius_norm_self_Tensor -XPtrTorchTensor cpp_torch_namespace_frobenius_norm_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_frobenius_norm_self_Tensor(SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_frobenius_norm_self_Tensor(self)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef XPtrTorchTensor cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP, SEXP keepdimSEXP) { @@ -24020,6 +23994,35 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view +Rcpp::List cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view(XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchstring_view reduce); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view(SEXP selfSEXP, SEXP otherSEXP, SEXP reduceSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type other(otherSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view(self, other, reduce)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2 +Rcpp::List cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2(XPtrTorchTensor self, XPtrTorchTensor grad_out, XPtrTorchTensor weight, XPtrTorchstring_view reduce, XPtrTorchTensor arg_out, std::vector output_mask); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2(SEXP selfSEXP, SEXP grad_outSEXP, SEXP weightSEXP, SEXP reduceSEXP, SEXP arg_outSEXP, SEXP output_maskSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out(grad_outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type arg_out(arg_outSEXP); + Rcpp::traits::input_parameter< std::vector >::type output_mask(output_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2(self, grad_out, weight, reduce, arg_out, output_mask)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor XPtrTorchTensor cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor mat1, XPtrTorchTensor mat2, XPtrTorchScalar beta, XPtrTorchScalar alpha); RcppExport SEXP _torch_cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP mat1SEXP, SEXP mat2SEXP, SEXP betaSEXP, SEXP alphaSEXP) { @@ -24562,8 +24565,8 @@ BEGIN_RCPP END_RCPP } // cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor -XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups); -RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(SEXP selfSEXP, SEXP paddingSEXP, SEXP strideSEXP, SEXP dilationSEXP, SEXP groupsSEXP) { +XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups, XPtrTorchOptionalIntArrayRef input_size); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(SEXP selfSEXP, SEXP paddingSEXP, SEXP strideSEXP, SEXP dilationSEXP, SEXP groupsSEXP, SEXP input_sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -24572,7 +24575,8 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type groups(groupsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(self, padding, stride, dilation, groups)); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type input_size(input_sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(self, padding, stride, dilation, groups, input_size)); return rcpp_result_gen; END_RCPP } @@ -25220,9 +25224,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool -Rcpp::List cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); -RcppExport SEXP _torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP grad_ySEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP z_stateSEXP, SEXP cell_state_fwdSEXP, SEXP inputSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { +// cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool +Rcpp::List cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensor layersOutputs, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); +RcppExport SEXP _torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP grad_ySEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP z_stateSEXP, SEXP cell_state_fwdSEXP, SEXP inputSEXP, SEXP layersOutputsSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -25232,6 +25236,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type z_state(z_stateSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type cell_state_fwd(cell_state_fwdSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type layersOutputs(layersOutputsSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type hx(hxSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type params(paramsSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); @@ -25240,7 +25245,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)); return rcpp_result_gen; END_RCPP } @@ -26666,19 +26671,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t -XPtrTorchTensor cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t(XPtrTorchTensor grad, XPtrTorchIntArrayRef input_sizes, XPtrTorchint64_t diagonal); -RcppExport SEXP _torch_cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t(SEXP gradSEXP, SEXP input_sizesSEXP, SEXP diagonalSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad(gradSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_sizes(input_sizesSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type diagonal(diagonalSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t(grad, input_sizes, diagonal)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchoptional_index_int64_t dim); RcppExport SEXP _torch_cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP, SEXP dimSEXP) { @@ -27808,47 +27800,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor -Rcpp::List cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor(XPtrTorchTensor e, XPtrTorchTensor V, XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor(SEXP eSEXP, SEXP VSEXP, SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type e(eSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type V(VSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor(e, V, self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_symeig_self_Tensor -Rcpp::List cpp_torch_namespace_symeig_self_Tensor(XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_namespace_symeig_self_Tensor(SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_symeig_self_Tensor(self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool -Rcpp::List cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool(XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool(SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool(self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor Rcpp::List cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor(XPtrTorchTensor U, XPtrTorchTensor S, XPtrTorchTensor V, XPtrTorchTensor self, XPtrTorchbool some, XPtrTorchbool compute_uv); RcppExport SEXP _torch_cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor(SEXP USEXP, SEXP SSEXP, SEXP VSEXP, SEXP selfSEXP, SEXP someSEXP, SEXP compute_uvSEXP) { @@ -28993,6 +28944,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_max_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_max_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_max_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_max_out_out_Tensor_self_Tensor(out, self)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_minimum_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_namespace_minimum_self_Tensor_other_Tensor(XPtrTorchTensor self, XPtrTorchTensor other); RcppExport SEXP _torch_cpp_torch_namespace_minimum_self_Tensor_other_Tensor(SEXP selfSEXP, SEXP otherSEXP) { @@ -29832,6 +29795,98 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar(self, scalar)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar(self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar(self, scalar)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar(self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar(self, scalar)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar(self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar(self, scalar)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar(self, scalar); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other, XPtrTorchScalar alpha); RcppExport SEXP _torch_cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP, SEXP alphaSEXP) { @@ -29928,6 +29983,98 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList(self, other)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList(self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList(self, other)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList(self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(self, other)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(self, other)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(self, other); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); RcppExport SEXP _torch_cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { @@ -30020,6 +30167,98 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar(self, scalars)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar(self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar(self, scalars)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar(self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar(self, scalars)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar(self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar(self, scalars)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar(self, scalars); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_exp_self_TensorList XPtrTorchTensorList cpp_torch_namespace__foreach_exp_self_TensorList(XPtrTorchTensorList self); RcppExport SEXP _torch_cpp_torch_namespace__foreach_exp_self_TensorList(SEXP selfSEXP) { @@ -30657,6 +30896,19 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +void cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(self, tensor1, tensor2, scalars); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar void cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars); RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { @@ -30670,6 +30922,19 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +void cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(self, tensor1, tensor2, scalars); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchScalar value); RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP valueSEXP) { @@ -30712,6 +30977,20 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(self, tensor1, tensor2, scalars)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar XPtrTorchTensorList cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars); RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { @@ -30726,64 +31005,82 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList -XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +XPtrTorchTensorList cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(self, other)); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(self, tensor1, tensor2, scalars)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList -void cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_norm_self_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_norm_self_TensorList(XPtrTorchTensorList self, XPtrTorchScalar ord); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_norm_self_TensorList(SEXP selfSEXP, SEXP ordSEXP) { BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(self, other); - return R_NilValue; + Rcpp::traits::input_parameter< XPtrTorchScalar >::type ord(ordSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_norm_self_TensorList(self, ord)); + return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList -XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList(SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(self, other)); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type weights(weightsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList(self, tensors1, weights)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList -void cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList +void cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList(SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightsSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(self, other); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type weights(weightsSEXP); + cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList(self, tensors1, weights); return R_NilValue; END_RCPP } -// cpp_torch_namespace__foreach_norm_self_TensorList -XPtrTorchTensorList cpp_torch_namespace__foreach_norm_self_TensorList(XPtrTorchTensorList self, XPtrTorchScalar ord); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_norm_self_TensorList(SEXP selfSEXP, SEXP ordSEXP) { +// cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar(XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar(SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchScalar >::type ord(ordSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_norm_self_TensorList(self, ord)); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type weight(weightSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar(self, tensors1, weight)); return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar +void cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar(XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar(SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type weight(weightSEXP); + cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar(self, tensors1, weight); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor XPtrTorchTensor cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor(XPtrTorchTensor self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right); RcppExport SEXP _torch_cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor(SEXP selfSEXP, SEXP boundariesSEXP, SEXP out_int32SEXP, SEXP rightSEXP) { @@ -30843,17 +31140,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor -XPtrTorchTensor cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor(SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor(self)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor XPtrTorchTensor cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor sorted_sequence, XPtrTorchTensor self, XPtrTorchbool out_int32, XPtrTorchbool right, XPtrTorchoptional_string_view side, XPtrTorchOptionalTensor sorter); RcppExport SEXP _torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor(SEXP outSEXP, SEXP sorted_sequenceSEXP, SEXP selfSEXP, SEXP out_int32SEXP, SEXP rightSEXP, SEXP sideSEXP, SEXP sorterSEXP) { @@ -33285,21 +33571,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33314,21 +33585,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33343,21 +33599,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33372,21 +33613,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33401,21 +33627,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33430,21 +33641,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { @@ -33471,34 +33667,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { @@ -33525,34 +33693,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { @@ -33579,34 +33719,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionaldouble scales); RcppExport SEXP _torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool(SEXP outSEXP, SEXP selfSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scalesSEXP) { @@ -38395,6 +38507,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef(self, dim)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_t_copy_self_Tensor XPtrTorchTensor cpp_torch_namespace_t_copy_self_Tensor(XPtrTorchTensor self); RcppExport SEXP _torch_cpp_torch_namespace_t_copy_self_Tensor(SEXP selfSEXP) { @@ -38531,254 +38655,16 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef size); -RcppExport SEXP _torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(SEXP selfSEXP, SEXP sizeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(self, size)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType -XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(XPtrTorchTensor self, XPtrTorchDtype dtype); -RcppExport SEXP _torch_cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(SEXP selfSEXP, SEXP dtypeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDtype >::type dtype(dtypeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(self, dtype)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t -XPtrTorchTensor cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step); -RcppExport SEXP _torch_cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(SEXP selfSEXP, SEXP dimensionSEXP, SEXP sizeSEXP, SEXP stepSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type dimension(dimensionSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type size(sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(self, dimension, size, step)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_alias_copy_self_Tensor -XPtrTorchTensor cpp_torch_namespace_alias_copy_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_alias_copy_self_Tensor(SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_alias_copy_self_Tensor(self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t -XPtrTorchTensor cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t level); -RcppExport SEXP _torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP levelSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type level(levelSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(out, self, level)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t -XPtrTorchTensor cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(XPtrTorchTensor out, XPtrTorchTensor primal, XPtrTorchTensor tangent, XPtrTorchint64_t level); -RcppExport SEXP _torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(SEXP outSEXP, SEXP primalSEXP, SEXP tangentSEXP, SEXP levelSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type primal(primalSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type tangent(tangentSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type level(levelSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(out, primal, tangent, level)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride, XPtrTorchoptional_int64_t storage_offset); -RcppExport SEXP _torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP, SEXP storage_offsetSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type storage_offset(storage_offsetSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(out, self, size, stride, storage_offset)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size); -RcppExport SEXP _torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t offset, XPtrTorchindex_int64_t dim1, XPtrTorchindex_int64_t dim2); -RcppExport SEXP _torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP offsetSEXP, SEXP dim1SEXP, SEXP dim2SEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type offset(offsetSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim1(dim1SEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim2(dim2SEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(out, self, offset, dim1, dim2)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchbool implicit); -RcppExport SEXP _torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP implicitSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type implicit(implicitSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size, implicit)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dims); -RcppExport SEXP _torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dims(dimsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(out, self, dims)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride); -RcppExport SEXP _torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(out, self, size, stride)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t -XPtrTorchTensor cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index); -RcppExport SEXP _torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP indexSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type index(indexSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(out, self, dim, index)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchoptional_int64_t start, XPtrTorchoptional_int64_t end, XPtrTorchint64_t step); -RcppExport SEXP _torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP startSEXP, SEXP endSEXP, SEXP stepSEXP) { +// cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor +void cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); +RcppExport SEXP _torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type start(startSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type end(endSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(out, self, dim, start, end, step)); - return rcpp_result_gen; + cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(out, self, dim); + return R_NilValue; END_RCPP } // cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t @@ -38807,204 +38693,52 @@ BEGIN_RCPP return R_NilValue; END_RCPP } -// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t -XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); -RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(out, self, dim)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t -XPtrTorchTensor cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim0, XPtrTorchindex_int64_t dim1); -RcppExport SEXP _torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dim0SEXP, SEXP dim1SEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim0(dim0SEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim1(dim1SEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(out, self, dim0, dim1)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t -XPtrTorchTensor cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); -RcppExport SEXP _torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(out, self, dim)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor -void cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); -RcppExport SEXP _torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { -BEGIN_RCPP - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(out, self, dim); - return R_NilValue; -END_RCPP -} -// cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size); -RcppExport SEXP _torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP) { +// cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef size); +RcppExport SEXP _torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(SEXP selfSEXP, SEXP sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(self, size)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType -XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDtype dtype); -RcppExport SEXP _torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(SEXP outSEXP, SEXP selfSEXP, SEXP dtypeSEXP) { +// cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType +XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(XPtrTorchTensor self, XPtrTorchDtype dtype); +RcppExport SEXP _torch_cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(SEXP selfSEXP, SEXP dtypeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchDtype >::type dtype(dtypeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(out, self, dtype)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(self, dtype)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t -XPtrTorchTensor cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step); -RcppExport SEXP _torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimensionSEXP, SEXP sizeSEXP, SEXP stepSEXP) { +// cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t +XPtrTorchTensor cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step); +RcppExport SEXP _torch_cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(SEXP selfSEXP, SEXP dimensionSEXP, SEXP sizeSEXP, SEXP stepSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type dimension(dimensionSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type size(sizeSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(out, self, dimension, size, step)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(self, dimension, size, step)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_alias_copy_self_Tensor +XPtrTorchTensor cpp_torch_namespace_alias_copy_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_alias_copy_self_Tensor(SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_alias_copy_self_Tensor(self)); return rcpp_result_gen; END_RCPP } @@ -39073,6 +38807,22 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor +XPtrTorchTensor cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal); +RcppExport SEXP _torch_cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type attn_mask(attn_maskSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, is_causal)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal); RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP need_attn_weightsSEXP, SEXP is_causalSEXP) { @@ -39090,9 +38840,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal); -RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP need_attn_weightsSEXP, SEXP is_causalSEXP) { +// cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor +XPtrTorchint64_t cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal); +RcppExport SEXP _torch_cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -39101,15 +38851,14 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type attn_mask(attn_maskSEXP); Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type need_attn_weights(need_attn_weightsSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, is_causal)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal); -RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP need_attn_weightsSEXP, SEXP is_causalSEXP) { +Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchOptionalTensor dropout_mask); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP dropout_maskSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -39118,9 +38867,176 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type attn_mask(attn_maskSEXP); Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type need_attn_weights(need_attn_weightsSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal)); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type dropout_mask(dropout_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor +Rcpp::List cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchbool return_debug_mask); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP return_debug_maskSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type return_debug_mask(return_debug_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor(query, key, value, dropout_p, is_causal, return_debug_mask)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t +Rcpp::List cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(XPtrTorchTensor grad_out, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchint64_t philox_seed, XPtrTorchint64_t philox_offset); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(SEXP grad_outSEXP, SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP outSEXP, SEXP logsumexpSEXP, SEXP cum_seq_qSEXP, SEXP cum_seq_kSEXP, SEXP max_qSEXP, SEXP max_kSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP philox_seedSEXP, SEXP philox_offsetSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out(grad_outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type logsumexp(logsumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_q(cum_seq_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_k(cum_seq_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_q(max_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_k(max_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type philox_seed(philox_seedSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type philox_offset(philox_offsetSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool +Rcpp::List cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchbool compute_log_sumexp, XPtrTorchbool is_causal); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP compute_log_sumexpSEXP, SEXP is_causalSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type compute_log_sumexp(compute_log_sumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool(query, key, value, compute_log_sumexp, is_causal)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor +Rcpp::List cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(XPtrTorchTensor grad_out_, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchbool is_causal, XPtrTorchbool chunk_grad_outputs); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(SEXP grad_out_SEXP, SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP outSEXP, SEXP logsumexpSEXP, SEXP is_causalSEXP, SEXP chunk_grad_outputsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out_(grad_out_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type logsumexp(logsumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type chunk_grad_outputs(chunk_grad_outputsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor +XPtrTorchbool cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchbool is_causal); +RcppExport SEXP _torch_cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP is_causalSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor(query, key, value, is_causal)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool +Rcpp::List cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchbool return_debug_mask); +RcppExport SEXP _torch_cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP cum_seq_qSEXP, SEXP cum_seq_kSEXP, SEXP max_qSEXP, SEXP max_kSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP return_debug_maskSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_q(cum_seq_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_k(cum_seq_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_q(max_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_k(max_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type return_debug_mask(return_debug_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t +Rcpp::List cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(XPtrTorchTensor grad_out, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchint64_t philox_seed, XPtrTorchint64_t philox_offset); +RcppExport SEXP _torch_cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(SEXP grad_outSEXP, SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP outSEXP, SEXP logsumexpSEXP, SEXP cum_seq_qSEXP, SEXP cum_seq_kSEXP, SEXP max_qSEXP, SEXP max_kSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP philox_seedSEXP, SEXP philox_offsetSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out(grad_outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type logsumexp(logsumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_q(cum_seq_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_k(cum_seq_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_q(max_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_k(max_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type philox_seed(philox_seedSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type philox_offset(philox_offsetSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t +Rcpp::List cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor cu_seqlens_q, XPtrTorchOptionalTensor cu_seqlens_k, XPtrTorchoptional_int64_t max_seqlen_q, XPtrTorchbool compute_log_sumexp, XPtrTorchbool causal); +RcppExport SEXP _torch_cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP cu_seqlens_qSEXP, SEXP cu_seqlens_kSEXP, SEXP max_seqlen_qSEXP, SEXP compute_log_sumexpSEXP, SEXP causalSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type cu_seqlens_q(cu_seqlens_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type cu_seqlens_k(cu_seqlens_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type max_seqlen_q(max_seqlen_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type compute_log_sumexp(compute_log_sumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type causal(causalSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor +Rcpp::List cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(XPtrTorchTensor grad_out_, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchbool is_causal, XPtrTorchbool chunk_grad_outputs); +RcppExport SEXP _torch_cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(SEXP grad_out_SEXP, SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP outSEXP, SEXP logsumexpSEXP, SEXP is_causalSEXP, SEXP chunk_grad_outputsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out_(grad_out_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type logsumexp(logsumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type chunk_grad_outputs(chunk_grad_outputsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs)); return rcpp_result_gen; END_RCPP } @@ -39181,25 +39097,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool -XPtrTorchTensor cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal); -RcppExport SEXP _torch_cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP cum_seq_qSEXP, SEXP cum_seq_kSEXP, SEXP max_qSEXP, SEXP max_kSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_q(cum_seq_qSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_k(cum_seq_kSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_q(max_qSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_k(max_kSEXP); - Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor Rcpp::List cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor(XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchOptionalTensor incr_key, XPtrTorchOptionalTensor incr_value); RcppExport SEXP _torch_cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor(SEXP srcSEXP, SEXP embed_dimSEXP, SEXP num_headsSEXP, SEXP qkv_weightSEXP, SEXP qkv_biasSEXP, SEXP proj_weightSEXP, SEXP proj_biasSEXP, SEXP use_geluSEXP, SEXP norm_firstSEXP, SEXP epsSEXP, SEXP norm_weight_1SEXP, SEXP norm_bias_1SEXP, SEXP norm_weight_2SEXP, SEXP norm_bias_2SEXP, SEXP ffn_weight_1SEXP, SEXP ffn_bias_1SEXP, SEXP ffn_weight_2SEXP, SEXP ffn_bias_2SEXP, SEXP maskSEXP, SEXP incr_keySEXP, SEXP incr_valueSEXP) { @@ -40446,6 +40343,30 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool +void cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf); +RcppExport SEXP _torch_cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(SEXP selfSEXP, SEXP gradsSEXP, SEXP exp_avgsSEXP, SEXP exp_avg_sqsSEXP, SEXP max_exp_avg_sqsSEXP, SEXP state_stepsSEXP, SEXP lrSEXP, SEXP beta1SEXP, SEXP beta2SEXP, SEXP weight_decaySEXP, SEXP epsSEXP, SEXP amsgradSEXP, SEXP maximizeSEXP, SEXP grad_scaleSEXP, SEXP found_infSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type grads(gradsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avgs(exp_avgsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avg_sqs(exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type max_exp_avg_sqs(max_exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type state_steps(state_stepsSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type lr(lrSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta1(beta1SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta2(beta2SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type weight_decay(weight_decaySEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type amsgrad(amsgradSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type maximize(maximizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_scale(grad_scaleSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type found_inf(found_infSEXP); + cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchint64_t self_num_batch_dims); RcppExport SEXP _torch_cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP, SEXP self_num_batch_dimsSEXP) { @@ -41290,6 +41211,24 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor +Rcpp::List cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor log_probs, XPtrTorchTensor targets, XPtrTorchTensor input_lengths, XPtrTorchTensor target_lengths, XPtrTorchint64_t blank, XPtrTorchbool zero_infinity); +RcppExport SEXP _torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor(SEXP out0SEXP, SEXP out1SEXP, SEXP log_probsSEXP, SEXP targetsSEXP, SEXP input_lengthsSEXP, SEXP target_lengthsSEXP, SEXP blankSEXP, SEXP zero_infinitySEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type log_probs(log_probsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type targets(targetsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input_lengths(input_lengthsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type target_lengths(target_lengthsSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type blank(blankSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type zero_infinity(zero_infinitySEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t XPtrTorchTensor cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t(XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor log_probs, XPtrTorchTensor targets, XPtrTorchIntArrayRef input_lengths, XPtrTorchIntArrayRef target_lengths, XPtrTorchTensor neg_log_likelihood, XPtrTorchTensor log_alpha, XPtrTorchint64_t blank, XPtrTorchbool zero_infinity); RcppExport SEXP _torch_cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t(SEXP outSEXP, SEXP gradSEXP, SEXP log_probsSEXP, SEXP targetsSEXP, SEXP input_lengthsSEXP, SEXP target_lengthsSEXP, SEXP neg_log_likelihoodSEXP, SEXP log_alphaSEXP, SEXP blankSEXP, SEXP zero_infinitySEXP) { @@ -42255,26 +42194,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); -RcppExport SEXP _torch_cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type ceil_mode(ceil_modeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef(out, self, kernel_size, stride, padding, dilation, ceil_mode)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); -RcppExport SEXP _torch_cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { +// cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); +RcppExport SEXP _torch_cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -42286,7 +42208,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type ceil_mode(ceil_modeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode)); return rcpp_result_gen; END_RCPP } @@ -42477,6 +42399,76 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor input, XPtrTorchTensor weight0, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor hx_, XPtrTorchTensor cx_, XPtrTorchbool reverse, XPtrTorchIntArrayRef batch_sizes, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool bidirectional, XPtrTorchbool batch_first, XPtrTorchbool train); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP out3SEXP, SEXP inputSEXP, SEXP weight0SEXP, SEXP weight1SEXP, SEXP weight2SEXP, SEXP weight3SEXP, SEXP hx_SEXP, SEXP cx_SEXP, SEXP reverseSEXP, SEXP batch_sizesSEXP, SEXP modeSEXP, SEXP hidden_sizeSEXP, SEXP num_layersSEXP, SEXP has_biasesSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP, SEXP trainSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out3(out3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight0(weight0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight1(weight1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight2(weight2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight3(weight3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hx_(hx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cx_(cx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type reverse(reverseSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type batch_sizes(batch_sizesSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type mode(modeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type hidden_size(hidden_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type num_layers(num_layersSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor out5, XPtrTorchTensor out6, XPtrTorchTensor input, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor weight4, XPtrTorchTensor hx_, XPtrTorchTensor cx_tmp, XPtrTorchTensor output, XPtrTorchTensor hy_, XPtrTorchTensor cy_, XPtrTorchOptionalTensor grad_output, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchbool reverse, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchIntArrayRef batch_sizes, XPtrTorchbool batch_first, XPtrTorchTensor workspace); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP out3SEXP, SEXP out4SEXP, SEXP out5SEXP, SEXP out6SEXP, SEXP inputSEXP, SEXP weight1SEXP, SEXP weight2SEXP, SEXP weight3SEXP, SEXP weight4SEXP, SEXP hx_SEXP, SEXP cx_tmpSEXP, SEXP outputSEXP, SEXP hy_SEXP, SEXP cy_SEXP, SEXP grad_outputSEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP reverseSEXP, SEXP modeSEXP, SEXP hidden_sizeSEXP, SEXP num_layersSEXP, SEXP has_biasesSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_sizesSEXP, SEXP batch_firstSEXP, SEXP workspaceSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out3(out3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out4(out4SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out5(out5SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out6(out6SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight1(weight1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight2(weight2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight3(weight3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight4(weight4SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hx_(hx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cx_tmp(cx_tmpSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type output(outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hy_(hy_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cy_(cy_SEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_output(grad_outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_hy(grad_hySEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_cy(grad_cySEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type reverse(reverseSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type mode(modeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type hidden_size(hidden_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type num_layers(num_layersSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type batch_sizes(batch_sizesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type workspace(workspaceSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double Rcpp::List cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor input, XPtrTorchTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchOptionalTensor running_mean, XPtrTorchOptionalTensor running_var, XPtrTorchbool training, XPtrTorchdouble exponential_average_factor, XPtrTorchdouble epsilon); RcppExport SEXP _torch_cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP exponential_average_factorSEXP, SEXP epsilonSEXP) { @@ -42656,19 +42648,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor -XPtrTorchTensor cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor(XPtrTorchTensor out, XPtrTorchTensor t, XPtrTorchTensor mask_indices); -RcppExport SEXP _torch_cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor(SEXP outSEXP, SEXP tSEXP, SEXP mask_indicesSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type t(tSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type mask_indices(mask_indicesSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor(out, t, mask_indices)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar XPtrTorchTensor cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchScalar other); RcppExport SEXP _torch_cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { @@ -42682,6 +42661,24 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_mean(running_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_var(running_varSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(input, weight, bias, running_mean, running_var, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double Rcpp::List cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor input, XPtrTorchdouble eps); RcppExport SEXP _torch_cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double(SEXP out0SEXP, SEXP out1SEXP, SEXP inputSEXP, SEXP epsSEXP) { @@ -43154,34 +43151,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor -XPtrTorchTensor cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight); -RcppExport SEXP _torch_cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor(out, self, weight)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor -Rcpp::List cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight); -RcppExport SEXP _torch_cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor(SEXP out0SEXP, SEXP out1SEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor(out0, out1, grad_output, self, weight)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t XPtrTorchTensor cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchIntArrayRef input_sizes, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index); RcppExport SEXP _torch_cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t(SEXP outSEXP, SEXP grad_outputSEXP, SEXP input_sizesSEXP, SEXP dimSEXP, SEXP indexSEXP) { @@ -43330,22 +43299,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t -Rcpp::List cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP out0SEXP, SEXP out1SEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(out0, out1, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_prod_out_out_Tensor_self_Tensor XPtrTorchTensor cpp_torch_namespace_prod_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype); RcppExport SEXP _torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dtypeSEXP) { @@ -43626,22 +43579,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t -Rcpp::List cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP out0SEXP, SEXP out1SEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(out0, out1, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor Rcpp::List cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor v, XPtrTorchTensor g, XPtrTorchindex_int64_t dim); RcppExport SEXP _torch_cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor(SEXP out0SEXP, SEXP out1SEXP, SEXP vSEXP, SEXP gSEXP, SEXP dimSEXP) { @@ -44328,64 +44265,71 @@ BEGIN_RCPP END_RCPP } // cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchLayout layout, XPtrTorchOptionalIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP layoutSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchLayout >::type layout(layoutSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type blocksize(blocksizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(out, self, layout, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(out, self, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(out, self, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP blocksizeSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type blocksize(blocksizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(out, self, blocksize)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(out, self, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP blocksizeSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type blocksize(blocksizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(out, self, blocksize)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(out, self, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } @@ -44403,8 +44347,8 @@ BEGIN_RCPP END_RCPP } // cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups); -RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP paddingSEXP, SEXP strideSEXP, SEXP dilationSEXP, SEXP groupsSEXP) { +XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups, XPtrTorchOptionalIntArrayRef input_size); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP paddingSEXP, SEXP strideSEXP, SEXP dilationSEXP, SEXP groupsSEXP, SEXP input_sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -44414,7 +44358,8 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type groups(groupsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(out, self, padding, stride, dilation, groups)); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type input_size(input_sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(out, self, padding, stride, dilation, groups, input_size)); return rcpp_result_gen; END_RCPP } @@ -44746,9 +44691,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool -Rcpp::List cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); -RcppExport SEXP _torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP out3SEXP, SEXP out4SEXP, SEXP inputSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { +// cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool +Rcpp::List cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor out5, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); +RcppExport SEXP _torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP out3SEXP, SEXP out4SEXP, SEXP out5SEXP, SEXP inputSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -44757,6 +44702,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type out3(out3SEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type out4(out4SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out5(out5SEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type hx(hxSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type params(paramsSEXP); @@ -44766,13 +44712,13 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool -void cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor out0, XPtrTorchTensorList out1, XPtrTorchTensorList out2, XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); -RcppExport SEXP _torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP grad_ySEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP z_stateSEXP, SEXP cell_state_fwdSEXP, SEXP inputSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { +// cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool +void cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor out0, XPtrTorchTensorList out1, XPtrTorchTensorList out2, XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensor layersOutputs, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); +RcppExport SEXP _torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP grad_ySEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP z_stateSEXP, SEXP cell_state_fwdSEXP, SEXP inputSEXP, SEXP layersOutputsSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); @@ -44784,6 +44730,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type z_state(z_stateSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type cell_state_fwd(cell_state_fwdSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type layersOutputs(layersOutputsSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type hx(hxSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type params(paramsSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); @@ -44792,7 +44739,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); - cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); + cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); return R_NilValue; END_RCPP } @@ -45507,21 +45454,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool -Rcpp::List cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool(out0, out1, self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool XPtrTorchTensor cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor A, XPtrTorchbool upper); RcppExport SEXP _torch_cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool(SEXP outSEXP, SEXP selfSEXP, SEXP ASEXP, SEXP upperSEXP) { @@ -45762,6 +45694,54 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar(out, self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar(out, self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar(out, self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar(out, self, scalar); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList void cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other, XPtrTorchScalar alpha); RcppExport SEXP _torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP, SEXP alphaSEXP) { @@ -45812,6 +45792,54 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar void cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); RcppExport SEXP _torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { @@ -45860,6 +45888,54 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(out, self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(out, self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(out, self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(out, self, scalars); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList void cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self); RcppExport SEXP _torch_cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList(SEXP outSEXP, SEXP selfSEXP) { @@ -46232,41 +46308,45 @@ BEGIN_RCPP return R_NilValue; END_RCPP } -// cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar -void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { +// cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +void cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); - Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); - cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(out, self, tensor1, tensor2, scalars); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(out, self, tensor1, tensor2, scalars); return R_NilValue; END_RCPP } -// cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList -void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(out, self, tensor1, tensor2, scalars); return R_NilValue; END_RCPP } -// cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList -void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(out, self, tensor1, tensor2, scalars); return R_NilValue; END_RCPP } @@ -46282,6 +46362,32 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList +void cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type weights(weightsSEXP); + cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList(out, self, tensors1, weights); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar +void cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type weight(weightSEXP); + cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar(out, self, tensors1, weight); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor XPtrTorchTensor cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor(XPtrTorchTensor out, XPtrTorchScalar self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right); RcppExport SEXP _torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP boundariesSEXP, SEXP out_int32SEXP, SEXP rightSEXP) { @@ -46297,18 +46403,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar XPtrTorchTensor cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar(XPtrTorchTensor out, XPtrTorchTensor sorted_sequence, XPtrTorchScalar self, XPtrTorchbool out_int32, XPtrTorchbool right, XPtrTorchoptional_string_view side, XPtrTorchOptionalTensor sorter); RcppExport SEXP _torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar(SEXP outSEXP, SEXP sorted_sequenceSEXP, SEXP selfSEXP, SEXP out_int32SEXP, SEXP rightSEXP, SEXP sideSEXP, SEXP sorterSEXP) { @@ -46454,614 +46548,657 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 +Rcpp::List cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, std::vector output_mask); +RcppExport SEXP _torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP output_maskSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); + Rcpp::traits::input_parameter< std::vector >::type output_mask(output_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); +RcppExport SEXP _torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); +RcppExport SEXP _torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); +RcppExport SEXP _torch_cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends); +RcppExport SEXP _torch_cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type addends(addendsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(out, values, addends)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends); +RcppExport SEXP _torch_cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type addends(addendsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(out, values, addends)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble +XPtrTorchTensor cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalDoubleArrayRef addends); +RcppExport SEXP _torch_cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type addends(addendsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(out, values, addends)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(out, self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(out, self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(out, self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view +XPtrTorchTensor cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(XPtrTorchTensor out, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchIndexTensor indices, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchbool unsafe, XPtrTorchoptional_scalar initial); +RcppExport SEXP _torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(SEXP outSEXP, SEXP dataSEXP, SEXP reduceSEXP, SEXP lengthsSEXP, SEXP indicesSEXP, SEXP offsetsSEXP, SEXP axisSEXP, SEXP unsafeSEXP, SEXP initialSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type data(dataSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type lengths(lengthsSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexTensor >::type indices(indicesSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type offsets(offsetsSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type axis(axisSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type unsafe(unsafeSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_scalar >::type initial(initialSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(out, data, reduce, lengths, indices, offsets, axis, unsafe, initial)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view +XPtrTorchTensor cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor output, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchoptional_scalar initial); +RcppExport SEXP _torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(SEXP outSEXP, SEXP gradSEXP, SEXP outputSEXP, SEXP dataSEXP, SEXP reduceSEXP, SEXP lengthsSEXP, SEXP offsetsSEXP, SEXP axisSEXP, SEXP initialSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad(gradSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type output(outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type data(dataSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type lengths(lengthsSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type offsets(offsetsSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type axis(axisSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_scalar >::type initial(initialSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(out, grad, output, data, reduce, lengths, offsets, axis, initial)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList +XPtrTorchTensor cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(XPtrTorchTensor out, XPtrTorchTensorList list, XPtrTorchoptional_scalar_type dtype, XPtrTorchLayout layout, XPtrTorchDevice device, XPtrTorchoptional_bool pin_memory); +RcppExport SEXP _torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(SEXP outSEXP, SEXP listSEXP, SEXP dtypeSEXP, SEXP layoutSEXP, SEXP deviceSEXP, SEXP pin_memorySEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type list(listSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_scalar_type >::type dtype(dtypeSEXP); + Rcpp::traits::input_parameter< XPtrTorchLayout >::type layout(layoutSEXP); + Rcpp::traits::input_parameter< XPtrTorchDevice >::type device(deviceSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_bool >::type pin_memory(pin_memorySEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(out, list, dtype, layout, device, pin_memory)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t +XPtrTorchTensor cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t level); +RcppExport SEXP _torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP levelSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type level(levelSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(out, self, level)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t +XPtrTorchTensor cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(XPtrTorchTensor out, XPtrTorchTensor primal, XPtrTorchTensor tangent, XPtrTorchint64_t level); +RcppExport SEXP _torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(SEXP outSEXP, SEXP primalSEXP, SEXP tangentSEXP, SEXP levelSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type primal(primalSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type tangent(tangentSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type level(levelSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(out, primal, tangent, level)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride, XPtrTorchoptional_int64_t storage_offset); +RcppExport SEXP _torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP, SEXP storage_offsetSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type storage_offset(storage_offsetSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(out, self, size, stride, storage_offset)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t offset, XPtrTorchindex_int64_t dim1, XPtrTorchindex_int64_t dim2); +RcppExport SEXP _torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP offsetSEXP, SEXP dim1SEXP, SEXP dim2SEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type offset(offsetSEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim1(dim1SEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim2(dim2SEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(out, self, offset, dim1, dim2)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchbool implicit); +RcppExport SEXP _torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP implicitSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type implicit(implicitSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size, implicit)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dims); +RcppExport SEXP _torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dims(dimsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(out, self, dims)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride); +RcppExport SEXP _torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(out, self, size, stride)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t +XPtrTorchTensor cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index); +RcppExport SEXP _torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP indexSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type index(indexSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(out, self, dim, index)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchoptional_int64_t start, XPtrTorchoptional_int64_t end, XPtrTorchint64_t step); +RcppExport SEXP _torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP startSEXP, SEXP endSEXP, SEXP stepSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type start(startSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type end(endSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(out, self, dim, start, end, step)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 -Rcpp::List cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, std::vector output_mask); -RcppExport SEXP _torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP output_maskSEXP) { +// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< std::vector >::type output_mask(output_maskSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask)); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(out, self, dim)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); -RcppExport SEXP _torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { +// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef(out, self, dim)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); -RcppExport SEXP _torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { +// cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); -RcppExport SEXP _torch_cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { +// cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t +XPtrTorchTensor cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim0, XPtrTorchindex_int64_t dim1); +RcppExport SEXP _torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dim0SEXP, SEXP dim1SEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim0(dim0SEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim1(dim1SEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(out, self, dim0, dim1)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t +XPtrTorchTensor cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); +RcppExport SEXP _torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(out, self, dim)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends); -RcppExport SEXP _torch_cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { +// cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type addends(addendsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(out, values, addends)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends); -RcppExport SEXP _torch_cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { +// cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type addends(addendsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(out, values, addends)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalDoubleArrayRef addends); -RcppExport SEXP _torch_cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { +// cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type addends(addendsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(out, values, addends)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view -XPtrTorchTensor cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(XPtrTorchTensor out, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchIndexTensor indices, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchbool unsafe, XPtrTorchoptional_scalar initial); -RcppExport SEXP _torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(SEXP outSEXP, SEXP dataSEXP, SEXP reduceSEXP, SEXP lengthsSEXP, SEXP indicesSEXP, SEXP offsetsSEXP, SEXP axisSEXP, SEXP unsafeSEXP, SEXP initialSEXP) { +// cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type data(dataSEXP); - Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type lengths(lengthsSEXP); - Rcpp::traits::input_parameter< XPtrTorchIndexTensor >::type indices(indicesSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type offsets(offsetsSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type axis(axisSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type unsafe(unsafeSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_scalar >::type initial(initialSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(out, data, reduce, lengths, indices, offsets, axis, unsafe, initial)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view -XPtrTorchTensor cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor output, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchoptional_scalar initial); -RcppExport SEXP _torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(SEXP outSEXP, SEXP gradSEXP, SEXP outputSEXP, SEXP dataSEXP, SEXP reduceSEXP, SEXP lengthsSEXP, SEXP offsetsSEXP, SEXP axisSEXP, SEXP initialSEXP) { +// cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size); +RcppExport SEXP _torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad(gradSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type output(outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type data(dataSEXP); - Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type lengths(lengthsSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type offsets(offsetsSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type axis(axisSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_scalar >::type initial(initialSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(out, grad, output, data, reduce, lengths, offsets, axis, initial)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList -XPtrTorchTensor cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(XPtrTorchTensor out, XPtrTorchTensorList list, XPtrTorchoptional_scalar_type dtype, XPtrTorchLayout layout, XPtrTorchDevice device, XPtrTorchoptional_bool pin_memory); -RcppExport SEXP _torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(SEXP outSEXP, SEXP listSEXP, SEXP dtypeSEXP, SEXP layoutSEXP, SEXP deviceSEXP, SEXP pin_memorySEXP) { +// cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType +XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDtype dtype); +RcppExport SEXP _torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(SEXP outSEXP, SEXP selfSEXP, SEXP dtypeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type list(listSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_scalar_type >::type dtype(dtypeSEXP); - Rcpp::traits::input_parameter< XPtrTorchLayout >::type layout(layoutSEXP); - Rcpp::traits::input_parameter< XPtrTorchDevice >::type device(deviceSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_bool >::type pin_memory(pin_memorySEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(out, list, dtype, layout, device, pin_memory)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchDtype >::type dtype(dtypeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(out, self, dtype)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t +XPtrTorchTensor cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step); +RcppExport SEXP _torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimensionSEXP, SEXP sizeSEXP, SEXP stepSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type dimension(dimensionSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type size(sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(out, self, dimension, size, step)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } @@ -47079,21 +47216,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double -XPtrTorchTensor cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchdouble eps); -RcppExport SEXP _torch_cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP epsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double(out, self, weight, bias, eps)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor XPtrTorchTensor cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor(XPtrTorchTensor out, XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchoptional_int64_t mask_type); RcppExport SEXP _torch_cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor(SEXP outSEXP, SEXP srcSEXP, SEXP embed_dimSEXP, SEXP num_headsSEXP, SEXP qkv_weightSEXP, SEXP qkv_biasSEXP, SEXP proj_weightSEXP, SEXP proj_biasSEXP, SEXP use_geluSEXP, SEXP norm_firstSEXP, SEXP epsSEXP, SEXP norm_weight_1SEXP, SEXP norm_bias_1SEXP, SEXP norm_weight_2SEXP, SEXP norm_bias_2SEXP, SEXP ffn_weight_1SEXP, SEXP ffn_bias_1SEXP, SEXP ffn_weight_2SEXP, SEXP ffn_bias_2SEXP, SEXP maskSEXP, SEXP mask_typeSEXP) { @@ -47313,6 +47435,56 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool +void cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf); +RcppExport SEXP _torch_cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(SEXP outSEXP, SEXP selfSEXP, SEXP gradsSEXP, SEXP exp_avgsSEXP, SEXP exp_avg_sqsSEXP, SEXP max_exp_avg_sqsSEXP, SEXP state_stepsSEXP, SEXP lrSEXP, SEXP beta1SEXP, SEXP beta2SEXP, SEXP weight_decaySEXP, SEXP epsSEXP, SEXP amsgradSEXP, SEXP maximizeSEXP, SEXP grad_scaleSEXP, SEXP found_infSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type grads(gradsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avgs(exp_avgsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avg_sqs(exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type max_exp_avg_sqs(max_exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type state_steps(state_stepsSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type lr(lrSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta1(beta1SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta2(beta2SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type weight_decay(weight_decaySEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type amsgrad(amsgradSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type maximize(maximizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_scale(grad_scaleSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type found_inf(found_infSEXP); + cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool +Rcpp::List cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf); +RcppExport SEXP _torch_cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(SEXP selfSEXP, SEXP gradsSEXP, SEXP exp_avgsSEXP, SEXP exp_avg_sqsSEXP, SEXP max_exp_avg_sqsSEXP, SEXP state_stepsSEXP, SEXP lrSEXP, SEXP beta1SEXP, SEXP beta2SEXP, SEXP weight_decaySEXP, SEXP epsSEXP, SEXP amsgradSEXP, SEXP maximizeSEXP, SEXP grad_scaleSEXP, SEXP found_infSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type grads(gradsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avgs(exp_avgsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avg_sqs(exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type max_exp_avg_sqs(max_exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type state_steps(state_stepsSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type lr(lrSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta1(beta1SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta2(beta2SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type weight_decay(weight_decaySEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type amsgrad(amsgradSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type maximize(maximizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_scale(grad_scaleSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type found_inf(found_infSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_generator XPtrTorchGenerator cpp_torch_generator(); RcppExport SEXP _torch_cpp_torch_generator() { @@ -49026,6 +49198,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_addmv__self_Tensor_mat_Tensor_vec_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addmv__self_Tensor_mat_Tensor_vec_Tensor, 5}, {"_torch_cpp_torch_method_addr_self_Tensor_vec1_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addr_self_Tensor_vec1_Tensor_vec2_Tensor, 5}, {"_torch_cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor, 5}, + {"_torch_cpp_torch_method__is_all_true_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method__is_all_true_self_Tensor, 1}, + {"_torch_cpp_torch_method__is_any_true_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method__is_any_true_self_Tensor, 1}, {"_torch_cpp_torch_method_all_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_all_self_Tensor_dim_int64_t, 3}, {"_torch_cpp_torch_method_all_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_all_self_Tensor_dim_Dimname, 3}, {"_torch_cpp_torch_method_allclose_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_method_allclose_self_Tensor_other_Tensor, 5}, @@ -49310,7 +49484,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_relu_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_relu_self_Tensor, 1}, {"_torch_cpp_torch_method_relu__self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_relu__self_Tensor, 1}, {"_torch_cpp_torch_method_prelu_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_method_prelu_self_Tensor_weight_Tensor, 2}, - {"_torch_cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor, 3}, {"_torch_cpp_torch_method_hardshrink_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_hardshrink_self_Tensor, 2}, {"_torch_cpp_torch_method_hardshrink_backward_grad_out_Tensor_self_Tensor_lambd_Scalar", (DL_FUNC) &_torch_cpp_torch_method_hardshrink_backward_grad_out_Tensor_self_Tensor_lambd_Scalar, 3}, {"_torch_cpp_torch_method_rsqrt_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_rsqrt_self_Tensor, 1}, @@ -49352,8 +49525,10 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_squeeze_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_squeeze_self_Tensor, 1}, {"_torch_cpp_torch_method_squeeze_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_squeeze_self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_method_squeeze_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_squeeze_self_Tensor_dim_Dimname, 2}, + {"_torch_cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef, 2}, {"_torch_cpp_torch_method_squeeze__self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_squeeze__self_Tensor, 1}, {"_torch_cpp_torch_method_squeeze__self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_squeeze__self_Tensor_dim_int64_t, 2}, + {"_torch_cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef, 2}, {"_torch_cpp_torch_method_squeeze__self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_squeeze__self_Tensor_dim_Dimname, 2}, {"_torch_cpp_torch_method_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, {"_torch_cpp_torch_method_stft_self_Tensor_n_fft_int64_t", (DL_FUNC) &_torch_cpp_torch_method_stft_self_Tensor_n_fft_int64_t, 10}, @@ -49371,9 +49546,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_square__self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_square__self_Tensor, 1}, {"_torch_cpp_torch_method_std_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor, 2}, {"_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList, 4}, - {"_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t, 4}, {"_torch_cpp_torch_method_prod_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_prod_self_Tensor, 2}, {"_torch_cpp_torch_method_prod_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_prod_self_Tensor_dim_int64_t, 4}, {"_torch_cpp_torch_method_prod_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_prod_self_Tensor_dim_Dimname, 4}, @@ -49404,11 +49577,10 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_unsqueeze__self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_unsqueeze__self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_method_var_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor, 2}, {"_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList, 4}, - {"_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t, 4}, {"_torch_cpp_torch_method_view_as_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_method_view_as_self_Tensor_other_Tensor, 2}, {"_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor, 3}, + {"_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar", (DL_FUNC) &_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar, 3}, {"_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType, 3}, {"_torch_cpp_torch_method_norm_self_Tensor_p_Scalar", (DL_FUNC) &_torch_cpp_torch_method_norm_self_Tensor_p_Scalar, 2}, {"_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dim_IntArrayRef_keepdim_bool_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dim_IntArrayRef_keepdim_bool_dtype_ScalarType, 5}, @@ -49458,11 +49630,11 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_unbind_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_unbind_self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_method_unbind_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_unbind_self_Tensor_dim_Dimname, 2}, {"_torch_cpp_torch_method_to_sparse_self_Tensor_sparse_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_self_Tensor_sparse_dim_int64_t, 2}, - {"_torch_cpp_torch_method_to_sparse_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_self_Tensor, 1}, - {"_torch_cpp_torch_method_to_sparse_csr_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_csr_self_Tensor, 1}, - {"_torch_cpp_torch_method_to_sparse_csc_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_csc_self_Tensor, 1}, - {"_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef, 2}, - {"_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef, 2}, + {"_torch_cpp_torch_method_to_sparse_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_self_Tensor, 4}, + {"_torch_cpp_torch_method_to_sparse_csr_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_csr_self_Tensor, 2}, + {"_torch_cpp_torch_method_to_sparse_csc_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_csc_self_Tensor, 2}, + {"_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef, 3}, + {"_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef, 3}, {"_torch_cpp_torch_method_to_mkldnn_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_mkldnn_self_Tensor, 2}, {"_torch_cpp_torch_method_dequantize_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_dequantize_self_Tensor, 1}, {"_torch_cpp_torch_method_q_scale_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_q_scale_self_Tensor, 1}, @@ -49642,7 +49814,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_addcdiv_self_Tensor_tensor1_Tensor_tensor2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addcdiv_self_Tensor_tensor1_Tensor_tensor2_Tensor, 4}, {"_torch_cpp_torch_method_addcdiv__self_Tensor_tensor1_Tensor_tensor2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addcdiv__self_Tensor_tensor1_Tensor_tensor2_Tensor, 4}, {"_torch_cpp_torch_method_triangular_solve_self_Tensor_A_Tensor", (DL_FUNC) &_torch_cpp_torch_method_triangular_solve_self_Tensor_A_Tensor, 5}, - {"_torch_cpp_torch_method_symeig_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_symeig_self_Tensor, 3}, {"_torch_cpp_torch_method_svd_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_svd_self_Tensor, 3}, {"_torch_cpp_torch_method_swapaxes_self_Tensor_axis0_int64_t_axis1_int64_t", (DL_FUNC) &_torch_cpp_torch_method_swapaxes_self_Tensor_axis0_int64_t_axis1_int64_t, 3}, {"_torch_cpp_torch_method_swapaxes__self_Tensor_axis0_int64_t_axis1_int64_t", (DL_FUNC) &_torch_cpp_torch_method_swapaxes__self_Tensor_axis0_int64_t_axis1_int64_t, 3}, @@ -49744,7 +49915,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_outer_self_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_outer_self_Tensor_vec2_Tensor, 2}, {"_torch_cpp_torch_method_ger_self_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_ger_self_Tensor_vec2_Tensor, 2}, {"_torch_cpp_torch_method_to_padded_tensor_self_Tensor_padding_double", (DL_FUNC) &_torch_cpp_torch_method_to_padded_tensor_self_Tensor_padding_double, 3}, - {"_torch_cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double, 4}, {"_torch_cpp_torch_namespace__cast_Byte_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__cast_Byte_self_Tensor, 2}, {"_torch_cpp_torch_namespace__cast_Char_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__cast_Char_self_Tensor, 2}, {"_torch_cpp_torch_namespace__cast_Double_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__cast_Double_self_Tensor, 2}, @@ -49833,6 +50003,9 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_addr_out_out_Tensor_self_Tensor_vec1_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_addr_out_out_Tensor_self_Tensor_vec1_Tensor_vec2_Tensor, 6}, {"_torch_cpp_torch_namespace_affine_grid_generator_theta_Tensor_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_affine_grid_generator_theta_Tensor_size_IntArrayRef_align_corners_bool, 3}, {"_torch_cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_size_IntArrayRef_align_corners_bool, 3}, + {"_torch_cpp_torch_namespace__is_all_true_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__is_all_true_self_Tensor, 1}, + {"_torch_cpp_torch_namespace__is_any_true_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__is_any_true_self_Tensor, 1}, + {"_torch_cpp_torch_namespace__test_check_tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__test_check_tensor_self_Tensor, 1}, {"_torch_cpp_torch_namespace_all_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_all_self_Tensor_dim_int64_t, 3}, {"_torch_cpp_torch_namespace_all_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_all_out_out_Tensor_self_Tensor_dim_int64_t, 4}, {"_torch_cpp_torch_namespace_all_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_namespace_all_self_Tensor_dim_Dimname, 3}, @@ -50322,8 +50495,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_max_pool1d_with_indices_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool1d_with_indices_self_Tensor_kernel_size_IntArrayRef, 6}, {"_torch_cpp_torch_namespace_max_pool1d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool1d_self_Tensor_kernel_size_IntArrayRef, 6}, {"_torch_cpp_torch_namespace_max_pool2d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool2d_self_Tensor_kernel_size_IntArrayRef, 6}, - {"_torch_cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef, 6}, - {"_torch_cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, + {"_torch_cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, {"_torch_cpp_torch_namespace_mkldnn_max_pool2d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool2d_self_Tensor_kernel_size_IntArrayRef, 6}, {"_torch_cpp_torch_namespace_mkldnn_max_pool2d_backward_grad_output_Tensor_output_Tensor_input_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool2d_backward_grad_output_Tensor_output_Tensor_input_Tensor_kernel_size_IntArrayRef, 8}, {"_torch_cpp_torch_namespace_mkldnn_max_pool3d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool3d_self_Tensor_kernel_size_IntArrayRef, 6}, @@ -50357,6 +50529,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__mps_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__mps_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t, 7}, {"_torch_cpp_torch_namespace_mps_convolution_backward_self_Tensor_grad_output_Tensor_weight_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_output_mask_stdarraybool3", (DL_FUNC) &_torch_cpp_torch_namespace_mps_convolution_backward_self_Tensor_grad_output_Tensor_weight_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_output_mask_stdarraybool3, 8}, {"_torch_cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t, 7}, + {"_torch_cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool, 16}, + {"_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor, 23}, {"_torch_cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double, 8}, {"_torch_cpp_torch_namespace_miopen_batch_norm_backward_input_Tensor_grad_output_Tensor_weight_Tensor_running_mean_Tensor_running_var_Tensor_save_mean_Tensor_save_var_Tensor_epsilon_double", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_batch_norm_backward_input_Tensor_grad_output_Tensor_weight_Tensor_running_mean_Tensor_running_var_Tensor_save_mean_Tensor_save_var_Tensor_epsilon_double, 8}, {"_torch_cpp_torch_namespace_miopen_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_benchmark_bool_deterministic_bool", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_benchmark_bool_deterministic_bool, 9}, @@ -50369,8 +50543,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_mm_self_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mm_self_Tensor_mat2_Tensor, 2}, {"_torch_cpp_torch_namespace_mm_out_out_Tensor_self_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mm_out_out_Tensor_self_Tensor_mat2_Tensor, 3}, {"_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor, 2}, + {"_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view, 3}, {"_torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor, 2}, - {"_torch_cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor, 2}, {"_torch_cpp_torch_namespace_mode_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_mode_self_Tensor_dim_int64_t, 3}, {"_torch_cpp_torch_namespace_mode_out_values_Tensor_indices_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_mode_out_values_Tensor_indices_Tensor_self_Tensor_dim_int64_t, 5}, {"_torch_cpp_torch_namespace_mode_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_namespace_mode_self_Tensor_dim_Dimname, 3}, @@ -50391,6 +50565,10 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_narrow_self_Tensor_dim_int64_t_start_Tensor_length_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_narrow_self_Tensor_dim_int64_t_start_Tensor_length_int64_t, 4}, {"_torch_cpp_torch_namespace_native_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_native_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 8}, {"_torch_cpp_torch_namespace_native_batch_norm_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_native_batch_norm_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 11}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 8}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 11}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double, 6}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double, 9}, {"_torch_cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double, 2}, {"_torch_cpp_torch_namespace_batch_norm_elemt_input_Tensor_weight_Tensor_bias_Tensor_mean_Tensor_invstd_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_elemt_input_Tensor_weight_Tensor_bias_Tensor_mean_Tensor_invstd_Tensor_eps_double, 6}, {"_torch_cpp_torch_namespace_batch_norm_elemt_out_out_Tensor_input_Tensor_weight_Tensor_bias_Tensor_mean_Tensor_invstd_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_elemt_out_out_Tensor_input_Tensor_weight_Tensor_bias_Tensor_mean_Tensor_invstd_Tensor_eps_double, 7}, @@ -50478,6 +50656,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_repeat_interleave_self_Tensor_repeats_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_repeat_interleave_self_Tensor_repeats_Tensor, 4}, {"_torch_cpp_torch_namespace_repeat_interleave_self_Tensor_repeats_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_repeat_interleave_self_Tensor_repeats_int64_t, 4}, {"_torch_cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef, 2}, + {"_torch_cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef, 2}, {"_torch_cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 3}, {"_torch_cpp_torch_namespace__mkldnn_reshape_self_Tensor_shape_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__mkldnn_reshape_self_Tensor_shape_IntArrayRef, 2}, {"_torch_cpp_torch_namespace_round_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_round_self_Tensor, 1}, @@ -50493,7 +50672,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_relu6_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_relu6_self_Tensor, 1}, {"_torch_cpp_torch_namespace_relu6__self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_relu6__self_Tensor, 1}, {"_torch_cpp_torch_namespace_prelu_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prelu_self_Tensor_weight_Tensor, 2}, - {"_torch_cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor, 3}, + {"_torch_cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor, 2}, + {"_torch_cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor, 3}, {"_torch_cpp_torch_namespace_gelu_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_gelu_out_out_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace_gelu__self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_gelu__self_Tensor, 2}, {"_torch_cpp_torch_namespace_gelu_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_gelu_self_Tensor, 2}, @@ -50571,6 +50751,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_squeeze_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_self_Tensor, 1}, {"_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname, 2}, + {"_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef, 2}, {"_torch_cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, {"_torch_cpp_torch_namespace_sspaddmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sspaddmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor, 6}, {"_torch_cpp_torch_namespace_stack_tensors_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace_stack_tensors_TensorList, 2}, @@ -50603,18 +50784,12 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_square_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_square_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_std_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor, 2}, {"_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_std_mean_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor, 2}, {"_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList, 4}, - {"_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef, 5}, - {"_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t, 5}, {"_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList, 4}, {"_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList, 5}, - {"_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t, 4}, - {"_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t, 5}, {"_torch_cpp_torch_namespace_prod_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prod_self_Tensor, 2}, {"_torch_cpp_torch_namespace_prod_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_prod_self_Tensor_dim_int64_t, 4}, {"_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor_dim_int64_t, 5}, @@ -50675,18 +50850,12 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_vander_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_vander_x_Tensor, 3}, {"_torch_cpp_torch_namespace_var_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor, 2}, {"_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef, 5}, - {"_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t, 5}, {"_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList, 4}, {"_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList, 5}, - {"_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t, 4}, - {"_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t, 5}, {"_torch_cpp_torch_namespace_var_mean_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor, 2}, {"_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList, 4}, - {"_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor, 3}, {"_torch_cpp_torch_namespace_where_out_out_Tensor_condition_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_where_out_out_Tensor_condition_Tensor_self_Tensor_other_Tensor, 4}, {"_torch_cpp_torch_namespace_where_condition_Tensor_self_Scalar_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_where_condition_Tensor_self_Scalar_other_Tensor, 3}, @@ -50739,7 +50908,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_norm_out_out_Tensor_self_Tensor_p_Scalar_dim_DimnameList_keepdim_bool", (DL_FUNC) &_torch_cpp_torch_namespace_norm_out_out_Tensor_self_Tensor_p_Scalar_dim_DimnameList_keepdim_bool, 5}, {"_torch_cpp_torch_namespace_frexp_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_frexp_self_Tensor, 1}, {"_torch_cpp_torch_namespace_frexp_out_mantissa_Tensor_exponent_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_frexp_out_mantissa_Tensor_exponent_Tensor_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_frobenius_norm_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_frobenius_norm_self_Tensor, 1}, {"_torch_cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef, 3}, {"_torch_cpp_torch_namespace_frobenius_norm_out_out_Tensor_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_frobenius_norm_out_out_Tensor_self_Tensor_dim_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_nuclear_norm_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_nuclear_norm_self_Tensor, 2}, @@ -50764,6 +50932,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__sparse_addmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_addmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, {"_torch_cpp_torch_namespace_sparse_sampled_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sparse_sampled_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor, 6}, {"_torch_cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, + {"_torch_cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view, 3}, + {"_torch_cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2, 6}, {"_torch_cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor, 6}, {"_torch_cpp_torch_namespace_addmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_addmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, {"_torch_cpp_torch_namespace__addmm_activation_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__addmm_activation_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor, 7}, @@ -50803,7 +50973,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_copy_sparse_to_sparse__self_Tensor_src_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_copy_sparse_to_sparse__self_Tensor_src_Tensor, 3}, {"_torch_cpp_torch_namespace_unbind_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_namespace_unbind_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_self_Tensor_dim_Dimname, 2}, - {"_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor, 5}, + {"_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor, 6}, {"_torch_cpp_torch_namespace_mkldnn_reorder_conv3d_weight_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv3d_weight_self_Tensor, 5}, {"_torch_cpp_torch_namespace_to_mkldnn_backward_grad_Tensor_input_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_mkldnn_backward_grad_Tensor_input_Tensor, 2}, {"_torch_cpp_torch_namespace_quantize_per_tensor_dynamic_self_Tensor_dtype_ScalarType_reduce_range_bool", (DL_FUNC) &_torch_cpp_torch_namespace_quantize_per_tensor_dynamic_self_Tensor_dtype_ScalarType_reduce_range_bool, 3}, @@ -50851,7 +51021,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_promote_types_type1_ScalarType_type2_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_promote_types_type1_ScalarType_type2_ScalarType, 2}, {"_torch_cpp_torch_namespace__local_scalar_dense_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__local_scalar_dense_self_Tensor, 1}, {"_torch_cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 9}, - {"_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 14}, + {"_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 15}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor, 5}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_impl_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_impl_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool, 6}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool, 6}, @@ -50950,7 +51120,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_addbmm_self_Tensor_batch1_Tensor_batch2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_addbmm_self_Tensor_batch1_Tensor_batch2_Tensor, 5}, {"_torch_cpp_torch_namespace_diag_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diag_out_out_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace_diag_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diag_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t, 3}, {"_torch_cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor, 4}, {"_torch_cpp_torch_namespace_cross_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_cross_self_Tensor_other_Tensor, 3}, {"_torch_cpp_torch_namespace_triu_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_triu_out_out_Tensor_self_Tensor, 3}, @@ -51038,9 +51207,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_linalg_solve_triangular_out_out_Tensor_self_Tensor_B_Tensor_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace_linalg_solve_triangular_out_out_Tensor_self_Tensor_B_Tensor_upper_bool, 6}, {"_torch_cpp_torch_namespace_linalg_solve_triangular_self_Tensor_B_Tensor_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace_linalg_solve_triangular_self_Tensor_B_Tensor_upper_bool, 5}, {"_torch_cpp_torch_namespace_linalg_vander_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_linalg_vander_x_Tensor, 2}, - {"_torch_cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor, 5}, - {"_torch_cpp_torch_namespace_symeig_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_symeig_self_Tensor, 3}, - {"_torch_cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool, 3}, {"_torch_cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor, 6}, {"_torch_cpp_torch_namespace_svd_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_svd_self_Tensor, 3}, {"_torch_cpp_torch_namespace_swapaxes_self_Tensor_axis0_int64_t_axis1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_swapaxes_self_Tensor_axis0_int64_t_axis1_int64_t, 3}, @@ -51129,6 +51295,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_maximum_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_maximum_out_out_Tensor_self_Tensor_other_Tensor, 3}, {"_torch_cpp_torch_namespace_max_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_max_self_Tensor_other_Tensor, 2}, {"_torch_cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor, 3}, + {"_torch_cpp_torch_namespace_max_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_max_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_minimum_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_minimum_self_Tensor_other_Tensor, 2}, {"_torch_cpp_torch_namespace_minimum_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_minimum_out_out_Tensor_self_Tensor_other_Tensor, 3}, {"_torch_cpp_torch_namespace_min_out_out_Tensor_other_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_min_out_out_Tensor_other_Tensor_self_Tensor, 3}, @@ -51192,6 +51359,14 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalar_Scalar, 2}, {"_torch_cpp_torch_namespace__foreach_div_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_self_TensorList_scalar_Scalar, 2}, {"_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar, 2}, {"_torch_cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList, 3}, {"_torch_cpp_torch_namespace__foreach_add__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add__self_TensorList_other_TensorList, 3}, {"_torch_cpp_torch_namespace__foreach_sub_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_self_TensorList_other_TensorList, 3}, @@ -51200,6 +51375,14 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_mul__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul__self_TensorList_other_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_div_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_self_TensorList_other_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_add__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add__self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_sub_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_self_TensorList_scalars_ArrayRefScalar, 2}, @@ -51208,6 +51391,14 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_mul_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul_self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_exp_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_exp_self_TensorList, 1}, {"_torch_cpp_torch_namespace__foreach_zero__self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_zero__self_TensorList, 1}, {"_torch_cpp_torch_namespace__foreach_exp__self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_exp__self_TensorList, 1}, @@ -51268,21 +51459,24 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 4}, + {"_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 4}, {"_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 4}, + {"_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 4}, {"_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 4}, + {"_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 4}, {"_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 4}, - {"_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList, 2}, - {"_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList, 2}, - {"_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList, 2}, - {"_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 4}, {"_torch_cpp_torch_namespace__foreach_norm_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_norm_self_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar, 3}, {"_torch_cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor, 4}, {"_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Tensor_boundaries_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Tensor_boundaries_Tensor, 5}, {"_torch_cpp_torch_namespace_bucketize_self_Scalar_boundaries_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_bucketize_self_Scalar_boundaries_Tensor, 4}, {"_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Tensor, 6}, - {"_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor, 1}, {"_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor, 7}, {"_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Scalar, 6}, {"_torch_cpp_torch_namespace__convert_indices_from_coo_to_csr_self_Tensor_size_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__convert_indices_from_coo_to_csr_self_Tensor_size_int64_t, 3}, @@ -51453,29 +51647,17 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__pad_enum_self_Tensor_pad_IntArrayRef_mode_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__pad_enum_self_Tensor_pad_IntArrayRef_mode_int64_t, 4}, {"_torch_cpp_torch_namespace_pad_self_Tensor_pad_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_pad_self_Tensor_pad_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, {"_torch_cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, - {"_torch_cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, {"_torch_cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, {"_torch_cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, - {"_torch_cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, {"_torch_cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, {"_torch_cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, - {"_torch_cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, {"_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool, 5}, {"_torch_cpp_torch_namespace_upsample_linear1d_self_Tensor_output_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_self_Tensor_output_size_IntArrayRef_align_corners_bool, 4}, {"_torch_cpp_torch_namespace_upsample_linear1d_backward_out_grad_input_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_backward_out_grad_input_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool, 6}, @@ -51828,6 +52010,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_split_with_sizes_copy_self_Tensor_split_sizes_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_split_with_sizes_copy_self_Tensor_split_sizes_IntArrayRef, 3}, {"_torch_cpp_torch_namespace_squeeze_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_self_Tensor, 1}, {"_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t, 2}, + {"_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef, 2}, {"_torch_cpp_torch_namespace_t_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_t_copy_self_Tensor, 1}, {"_torch_cpp_torch_namespace_transpose_copy_self_Tensor_dim0_int64_t_dim1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_transpose_copy_self_Tensor_dim0_int64_t_dim1_int64_t, 3}, {"_torch_cpp_torch_namespace_unsqueeze_copy_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unsqueeze_copy_self_Tensor_dim_int64_t, 2}, @@ -51840,54 +52023,33 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_ccol_indices_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_ccol_indices_copy_self_Tensor, 1}, {"_torch_cpp_torch_namespace_row_indices_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_row_indices_copy_self_Tensor, 1}, {"_torch_cpp_torch_namespace_unbind_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_copy_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor, 3}, + {"_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t, 4}, + {"_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef, 2}, {"_torch_cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType, 2}, {"_torch_cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t, 4}, {"_torch_cpp_torch_namespace_alias_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_alias_copy_self_Tensor, 1}, - {"_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t, 3}, - {"_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t, 4}, - {"_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 5}, - {"_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor, 5}, - {"_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t, 4}, - {"_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor, 6}, - {"_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t, 4}, - {"_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t, 3}, - {"_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t, 4}, - {"_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t, 3}, - {"_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType, 3}, - {"_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t, 5}, - {"_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor, 2}, {"_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor, 20}, {"_torch_cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor, 13}, + {"_torch_cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor, 6}, {"_torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor, 7}, - {"_torch_cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor, 7}, + {"_torch_cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor, 6}, {"_torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor, 7}, + {"_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor, 6}, + {"_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t, 14}, + {"_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool, 5}, + {"_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor, 8}, + {"_torch_cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor, 4}, + {"_torch_cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool", (DL_FUNC) &_torch_cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool, 10}, + {"_torch_cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t, 14}, + {"_torch_cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t, 8}, + {"_torch_cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor, 8}, {"_torch_cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor, 4}, {"_torch_cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor, 10}, {"_torch_cpp_torch_namespace_special_airy_ai_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_special_airy_ai_x_Tensor, 1}, {"_torch_cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor, 2}, - {"_torch_cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool", (DL_FUNC) &_torch_cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool, 9}, {"_torch_cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor, 21}, {"_torch_cpp_torch_namespace__native_decoder_only_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__native_decoder_only_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor, 14}, {"_torch_cpp_torch_namespace_special_bessel_j0_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_special_bessel_j0_self_Tensor, 1}, @@ -51986,6 +52148,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_special_spherical_bessel_j0_out_out_Tensor_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_special_spherical_bessel_j0_out_out_Tensor_x_Tensor, 2}, {"_torch_cpp_torch_namespace__foobar_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foobar_self_Tensor, 4}, {"_torch_cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 15}, + {"_torch_cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 15}, {"_torch_cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor, 4}, {"_torch_cpp_torch_namespace__cudnn_ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_blank_int64_t_deterministic_bool_zero_infinity_bool", (DL_FUNC) &_torch_cpp_torch_namespace__cudnn_ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_blank_int64_t_deterministic_bool_zero_infinity_bool, 9}, {"_torch_cpp_torch_namespace__cudnn_rnn_flatten_weight_out_out_Tensor_weight_arr_TensorList_weight_stride0_int64_t_input_size_int64_t_mode_int64_t_hidden_size_int64_t_proj_size_int64_t_num_layers_int64_t_batch_first_bool_bidirectional_bool", (DL_FUNC) &_torch_cpp_torch_namespace__cudnn_rnn_flatten_weight_out_out_Tensor_weight_arr_TensorList_weight_stride0_int64_t_input_size_int64_t_mode_int64_t_hidden_size_int64_t_proj_size_int64_t_num_layers_int64_t_batch_first_bool_bidirectional_bool, 10}, @@ -52036,6 +52199,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_cudnn_grid_sampler_out_out_Tensor_self_Tensor_grid_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_cudnn_grid_sampler_out_out_Tensor_self_Tensor_grid_Tensor, 3}, {"_torch_cpp_torch_namespace_cudnn_grid_sampler_backward_out_out0_Tensor_out1_Tensor_self_Tensor_grid_Tensor_grad_output_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_cudnn_grid_sampler_backward_out_out0_Tensor_out1_Tensor_self_Tensor_grid_Tensor_grad_output_Tensor, 5}, {"_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef, 8}, + {"_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor, 8}, {"_torch_cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t, 10}, {"_torch_cpp_torch_namespace_diag_embed_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diag_embed_out_out_Tensor_self_Tensor, 5}, {"_torch_cpp_torch_namespace_diagonal_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_offset_int64_t_dim1_int64_t_dim2_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_diagonal_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_offset_int64_t_dim1_int64_t_dim2_int64_t, 6}, @@ -52099,8 +52263,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_matmul_backward_out_out0_Tensor_out1_Tensor_grad_Tensor_self_Tensor_other_Tensor_mask_stdarraybool2", (DL_FUNC) &_torch_cpp_torch_namespace_matmul_backward_out_out0_Tensor_out1_Tensor_grad_Tensor_self_Tensor_other_Tensor_mask_stdarraybool2, 6}, {"_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor_dim_int64_t, 5}, - {"_torch_cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, - {"_torch_cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef, 8}, + {"_torch_cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef, 8}, {"_torch_cpp_torch_namespace_mkldnn_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, {"_torch_cpp_torch_namespace_mkldnn_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_output_Tensor_input_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_output_Tensor_input_Tensor_kernel_size_IntArrayRef, 9}, {"_torch_cpp_torch_namespace_mkldnn_max_pool3d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool3d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, @@ -52112,6 +52275,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__mps_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__mps_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t, 8}, {"_torch_cpp_torch_namespace_mps_convolution_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor_grad_output_Tensor_weight_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_output_mask_stdarraybool3", (DL_FUNC) &_torch_cpp_torch_namespace_mps_convolution_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor_grad_output_Tensor_weight_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_output_mask_stdarraybool3, 11}, {"_torch_cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t, 8}, + {"_torch_cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool, 20}, + {"_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor, 30}, {"_torch_cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double, 11}, {"_torch_cpp_torch_namespace_miopen_batch_norm_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_grad_output_Tensor_weight_Tensor_running_mean_Tensor_running_var_Tensor_save_mean_Tensor_save_var_Tensor_epsilon_double", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_batch_norm_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_grad_output_Tensor_weight_Tensor_running_mean_Tensor_running_var_Tensor_save_mean_Tensor_save_var_Tensor_epsilon_double, 11}, {"_torch_cpp_torch_namespace_miopen_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_benchmark_bool_deterministic_bool", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_benchmark_bool_deterministic_bool, 10}, @@ -52120,8 +52285,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_miopen_rnn_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_weight_TensorList_weight_stride0_int64_t_hx_Tensor_cx_Tensor_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_batch_first_bool_dropout_double_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_dropout_state_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_rnn_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_weight_TensorList_weight_stride0_int64_t_hx_Tensor_cx_Tensor_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_batch_first_bool_dropout_double_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_dropout_state_Tensor, 19}, {"_torch_cpp_torch_namespace_miopen_rnn_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_TensorList_input_Tensor_weight_TensorList_weight_stride0_int64_t_weight_buf_Tensor_hx_Tensor_cx_Tensor_output_Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_batch_first_bool_dropout_double_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_dropout_state_Tensor_reserve_Tensor_output_mask_stdarraybool4", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_rnn_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_TensorList_input_Tensor_weight_TensorList_weight_stride0_int64_t_weight_buf_Tensor_hx_Tensor_cx_Tensor_output_Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_batch_first_bool_dropout_double_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_dropout_state_Tensor_reserve_Tensor_output_mask_stdarraybool4, 25}, {"_torch_cpp_torch_namespace__sparse_sparse_matmul_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_sparse_matmul_out_out_Tensor_self_Tensor_other_Tensor, 3}, - {"_torch_cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor, 3}, {"_torch_cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar, 3}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 8}, {"_torch_cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double, 4}, {"_torch_cpp_torch_namespace_batch_norm_gather_stats_out_out0_Tensor_out1_Tensor_input_Tensor_mean_Tensor_invstd_Tensor_running_mean_Tensor_running_var_Tensor_momentum_double_eps_double_count_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_gather_stats_out_out0_Tensor_out1_Tensor_input_Tensor_mean_Tensor_invstd_Tensor_running_mean_Tensor_running_var_Tensor_momentum_double_eps_double_count_int64_t, 10}, {"_torch_cpp_torch_namespace_batch_norm_gather_stats_with_counts_out_out0_Tensor_out1_Tensor_input_Tensor_mean_Tensor_invstd_Tensor_running_mean_Tensor_running_var_Tensor_momentum_double_eps_double_counts_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_gather_stats_with_counts_out_out0_Tensor_out1_Tensor_input_Tensor_mean_Tensor_invstd_Tensor_running_mean_Tensor_running_var_Tensor_momentum_double_eps_double_counts_Tensor, 10}, @@ -52154,8 +52319,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_repeat_interleave_out_out_Tensor_repeats_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_repeat_interleave_out_out_Tensor_repeats_Tensor, 3}, {"_torch_cpp_torch_namespace__mkldnn_reshape_out_out_Tensor_self_Tensor_shape_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__mkldnn_reshape_out_out_Tensor_self_Tensor_shape_IntArrayRef, 3}, {"_torch_cpp_torch_namespace_relu_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_relu_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor, 3}, - {"_torch_cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor, 5}, {"_torch_cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t, 5}, {"_torch_cpp_torch_namespace_celu_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_celu_out_out_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace_slice_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_start_int64_t_end_int64_t_step_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_slice_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_start_int64_t_end_int64_t_step_int64_t, 7}, @@ -52166,7 +52329,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_unsafe_split_out_out_TensorList_self_Tensor_split_size_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unsafe_split_out_out_TensorList_self_Tensor_split_size_int64_t, 4}, {"_torch_cpp_torch_namespace_unsafe_split_with_sizes_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_unsafe_split_with_sizes_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_sum_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sum_out_out_Tensor_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t, 6}, {"_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace__mkldnn_transpose_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__mkldnn_transpose_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t, 4}, {"_torch_cpp_torch_namespace_flip_out_out_Tensor_self_Tensor_dims_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_flip_out_out_Tensor_self_Tensor_dims_IntArrayRef, 3}, @@ -52186,7 +52348,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_unique_dim_consecutive_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unique_dim_consecutive_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor_dim_int64_t, 7}, {"_torch_cpp_torch_namespace__unique2_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__unique2_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor, 7}, {"_torch_cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t, 6}, {"_torch_cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor, 5}, {"_torch_cpp_torch_namespace__weight_norm_interface_backward_out_out0_Tensor_out1_Tensor_grad_w_Tensor_saved_v_Tensor_saved_g_Tensor_saved_norms_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__weight_norm_interface_backward_out_out0_Tensor_out1_Tensor_grad_w_Tensor_saved_v_Tensor_saved_g_Tensor_saved_norms_Tensor_dim_int64_t, 7}, {"_torch_cpp_torch_namespace_zeros_out_out_Tensor_size_IntArrayRef_names_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_zeros_out_out_Tensor_size_IntArrayRef_names_DimnameList, 3}, @@ -52237,13 +52398,13 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_copy_sparse_to_sparse_out_out_Tensor_self_Tensor_src_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_copy_sparse_to_sparse_out_out_Tensor_self_Tensor_src_Tensor, 4}, {"_torch_cpp_torch_namespace_copy_sparse_to_sparse_self_Tensor_src_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_copy_sparse_to_sparse_self_Tensor_src_Tensor, 3}, {"_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor_sparse_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor_sparse_dim_int64_t, 3}, - {"_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor, 5}, + {"_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor, 3}, + {"_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor, 3}, + {"_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef, 4}, + {"_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_to_mkldnn_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_mkldnn_out_out_Tensor_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor, 6}, + {"_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor, 7}, {"_torch_cpp_torch_namespace_mkldnn_reorder_conv3d_weight_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv3d_weight_out_out_Tensor_self_Tensor, 6}, {"_torch_cpp_torch_namespace_quantize_per_tensor_dynamic_out_out_Tensor_self_Tensor_dtype_ScalarType_reduce_range_bool", (DL_FUNC) &_torch_cpp_torch_namespace_quantize_per_tensor_dynamic_out_out_Tensor_self_Tensor_dtype_ScalarType_reduce_range_bool, 4}, {"_torch_cpp_torch_namespace_quantize_per_tensor_out_out_Tensor_self_Tensor_scale_double_zero_point_int64_t_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_quantize_per_tensor_out_out_Tensor_self_Tensor_scale_double_zero_point_int64_t_dtype_ScalarType, 5}, @@ -52265,8 +52426,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__fused_moving_avg_obs_fq_helper_out_out0_Tensor_out1_Tensor_self_Tensor_observer_on_Tensor_fake_quant_on_Tensor_running_min_Tensor_running_max_Tensor_scale_Tensor_zero_point_Tensor_averaging_const_double_quant_min_int64_t_quant_max_int64_t_ch_axis_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__fused_moving_avg_obs_fq_helper_out_out0_Tensor_out1_Tensor_self_Tensor_observer_on_Tensor_fake_quant_on_Tensor_running_min_Tensor_running_max_Tensor_scale_Tensor_zero_point_Tensor_averaging_const_double_quant_min_int64_t_quant_max_int64_t_ch_axis_int64_t, 15}, {"_torch_cpp_torch_namespace__fused_moving_avg_obs_fq_helper_functional_self_Tensor_observer_on_Tensor_fake_quant_on_Tensor_running_min_Tensor_running_max_Tensor_scale_Tensor_zero_point_Tensor_averaging_const_double_quant_min_int64_t_quant_max_int64_t_ch_axis_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__fused_moving_avg_obs_fq_helper_functional_self_Tensor_observer_on_Tensor_fake_quant_on_Tensor_running_min_Tensor_running_max_Tensor_scale_Tensor_zero_point_Tensor_averaging_const_double_quant_min_int64_t_quant_max_int64_t_ch_axis_int64_t, 13}, {"_torch_cpp_torch_namespace__to_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__to_copy_out_out_Tensor_self_Tensor, 4}, - {"_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 14}, - {"_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 17}, + {"_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 15}, + {"_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 18}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_out_out0_Tensor_out1_Tensor_out2_Tensor_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_out_out0_Tensor_out1_Tensor_out2_Tensor_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor, 8}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_impl_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_impl_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool, 9}, {"_torch_cpp_torch_namespace__thnn_fused_gru_cell_out_out0_Tensor_out1_Tensor_input_gates_Tensor_hidden_gates_Tensor_hx_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_gru_cell_out_out0_Tensor_out1_Tensor_input_gates_Tensor_hidden_gates_Tensor_hx_Tensor, 7}, @@ -52318,7 +52479,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_tril_indices_out_out_Tensor_row_int64_t_col_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_tril_indices_out_out_Tensor_row_int64_t_col_int64_t, 4}, {"_torch_cpp_torch_namespace_triu_indices_out_out_Tensor_row_int64_t_col_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_triu_indices_out_out_Tensor_row_int64_t_col_int64_t, 4}, {"_torch_cpp_torch_namespace_trace_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_trace_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool, 5}, {"_torch_cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool, 4}, {"_torch_cpp_torch_namespace_dist_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_dist_out_out_Tensor_self_Tensor_other_Tensor, 4}, {"_torch_cpp_torch_namespace__histogramdd_bin_edges_out_out_TensorList_self_Tensor_bins_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__histogramdd_bin_edges_out_out_TensorList_self_Tensor_bins_IntArrayRef, 6}, @@ -52336,14 +52496,26 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, {"_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, {"_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, {"_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_other_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_other_TensorList, 3}, {"_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList, 3}, {"_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, {"_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, {"_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, {"_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, + {"_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, + {"_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, {"_torch_cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_zero_out_out_TensorList_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_zero_out_out_TensorList_self_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_zero_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_zero_self_TensorList, 1}, @@ -52377,12 +52549,13 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList, 5}, {"_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList, 5}, {"_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 5}, + {"_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 5}, {"_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 5}, - {"_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList, 3}, - {"_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 5}, {"_torch_cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList, 4}, + {"_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar, 4}, {"_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor, 5}, - {"_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar, 7}, {"_torch_cpp_torch_namespace_glu_jvp_out_out_Tensor_glu_Tensor_x_Tensor_dx_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_glu_jvp_out_out_Tensor_glu_Tensor_x_Tensor_dx_Tensor_dim_int64_t, 5}, {"_torch_cpp_torch_namespace_glu_backward_jvp_out_out_Tensor_grad_x_Tensor_grad_glu_Tensor_x_Tensor_dgrad_glu_Tensor_dx_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_glu_backward_jvp_out_out_Tensor_grad_x_Tensor_grad_glu_Tensor_x_Tensor_dgrad_glu_Tensor_dx_Tensor_dim_int64_t, 7}, @@ -52393,30 +52566,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__adaptive_avg_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__adaptive_avg_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace__adaptive_avg_pool3d_out_out_Tensor_self_Tensor_output_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__adaptive_avg_pool3d_out_out_Tensor_self_Tensor_output_size_IntArrayRef, 3}, {"_torch_cpp_torch_namespace__adaptive_avg_pool3d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__adaptive_avg_pool3d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3", (DL_FUNC) &_torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3, 10}, {"_torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef, 8}, {"_torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef, 8}, @@ -52432,10 +52581,40 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view", (DL_FUNC) &_torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view, 9}, {"_torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view", (DL_FUNC) &_torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view, 9}, {"_torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList, 6}, + {"_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t, 3}, + {"_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t, 4}, + {"_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 5}, + {"_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor, 5}, + {"_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 4}, + {"_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 4}, + {"_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t, 4}, + {"_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor, 6}, + {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t, 3}, + {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t, 4}, + {"_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t, 3}, + {"_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType, 3}, + {"_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t, 5}, + {"_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double", (DL_FUNC) &_torch_cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double, 4}, - {"_torch_cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double, 5}, {"_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor, 21}, {"_torch_cpp_torch_namespace__native_multi_head_attention_out_out0_Tensor_out1_Tensor_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__native_multi_head_attention_out_out0_Tensor_out1_Tensor_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor, 15}, {"_torch_cpp_torch_namespace__triton_scaled_dot_attention_out_out_Tensor_q_Tensor_k_Tensor_v_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__triton_scaled_dot_attention_out_out_Tensor_q_Tensor_k_Tensor_v_Tensor, 5}, @@ -52445,6 +52624,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foobar_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foobar_out_out_Tensor_self_Tensor, 5}, {"_torch_cpp_torch_namespace__fused_adam_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adam_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 16}, {"_torch_cpp_torch_namespace__fused_adam_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adam_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 15}, + {"_torch_cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 16}, + {"_torch_cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 15}, {"_torch_cpp_torch_generator", (DL_FUNC) &_torch_cpp_torch_generator, 0}, {"_torch_cpp_generator_current_seed", (DL_FUNC) &_torch_cpp_generator_current_seed, 1}, {"_torch_cpp_generator_set_current_seed", (DL_FUNC) &_torch_cpp_generator_set_current_seed, 2}, diff --git a/src/gen-namespace.cpp b/src/gen-namespace.cpp index c7f056132a..10af3c7375 100644 --- a/src/gen-namespace.cpp +++ b/src/gen-namespace.cpp @@ -257,6 +257,18 @@ XPtrTorchTensor cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor (XPtr return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method__is_all_true_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern_Tensor__is_all_true_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method__is_any_true_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern_Tensor__is_any_true_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_all_self_Tensor_dim_int64_t (XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchbool keepdim) { auto r_out = lantern_Tensor_all_tensor_intt_bool(self.get(), dim.get(), keepdim.get()); @@ -1978,13 +1990,6 @@ XPtrTorchTensor cpp_torch_method_prelu_self_Tensor_weight_Tensor (XPtrTorchTenso return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight) { - auto r_out = lantern_Tensor_prelu_backward_tensor_tensor_tensor(grad_output.get(), self.get(), weight.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_hardshrink_self_Tensor (XPtrTorchTensor self, XPtrTorchScalar lambd) { auto r_out = lantern_Tensor_hardshrink_tensor_scalar(self.get(), lambd.get()); @@ -2231,6 +2236,12 @@ XPtrTorchTensor cpp_torch_method_squeeze_self_Tensor_dim_Dimname (XPtrTorchTenso return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_Tensor_squeeze_tensor_intarrayref(self.get(), dim.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor (XPtrTorchTensor self) { auto r_out = lantern_Tensor_squeeze__tensor(self.get()); @@ -2243,6 +2254,12 @@ XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_int64_t (XPtrTorchTens return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_Tensor_squeeze__tensor_intarrayref(self.get(), dim.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_Dimname (XPtrTorchTensor self, XPtrTorchDimname dim) { auto r_out = lantern_Tensor_squeeze__tensor_dimname(self.get(), dim.get()); @@ -2345,24 +2362,12 @@ XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_IntArrayRef (XPtrTorchTenso return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_Tensor_std_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_Tensor_std_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_Tensor_std_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_prod_self_Tensor (XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype) { auto r_out = lantern_Tensor_prod_tensor_scalartype(self.get(), dtype.get()); @@ -2543,24 +2548,12 @@ XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_IntArrayRef (XPtrTorchTenso return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_Tensor_var_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_Tensor_var_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_Tensor_var_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_view_as_self_Tensor_other_Tensor (XPtrTorchTensor self, XPtrTorchTensor other) { auto r_out = lantern_Tensor_view_as_tensor_tensor(self.get(), other.get()); @@ -2573,6 +2566,12 @@ XPtrTorchTensor cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar (XPtrTorchTensor condition, XPtrTorchTensor self, XPtrTorchScalar other) { + auto r_out = lantern_Tensor_where_tensor_tensor_scalar(condition.get(), self.get(), other.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType (XPtrTorchTensor self, XPtrTorchoptional_scalar p, XPtrTorchDtype dtype) { auto r_out = lantern_Tensor_norm_tensor_scalar_scalartype(self.get(), p.get(), dtype.get()); @@ -2869,32 +2868,32 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern_Tensor_to_sparse_tensor(self.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_self_Tensor (XPtrTorchTensor self, XPtrTorchLayout layout, XPtrTorchOptionalIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(self.get(), layout.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_csr_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern_Tensor_to_sparse_csr_tensor(self.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_csr_self_Tensor (XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_csr_tensor_intt(self.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_csc_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern_Tensor_to_sparse_csc_tensor(self.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_csc_self_Tensor (XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_csc_tensor_intt(self.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize) { - auto r_out = lantern_Tensor_to_sparse_bsr_tensor_intarrayref(self.get(), blocksize.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(self.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize) { - auto r_out = lantern_Tensor_to_sparse_bsc_tensor_intarrayref(self.get(), blocksize.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(self.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } @@ -3973,13 +3972,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_method_symeig_self_Tensor (XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern_Tensor_symeig_tensor_bool_bool(self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_method_svd_self_Tensor (XPtrTorchTensor self, XPtrTorchbool some, XPtrTorchbool compute_uv) { auto r_out = lantern_Tensor_svd_tensor_bool_bool(self.get(), some.get(), compute_uv.get()); @@ -4596,12 +4588,6 @@ XPtrTorchTensor cpp_torch_method_to_padded_tensor_self_Tensor_padding_double (XP return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double (XPtrTorchTensor self, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchdouble eps) { - auto r_out = lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(self.get(), weight.get(), bias.get(), eps.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__cast_Byte_self_Tensor (XPtrTorchTensor self, XPtrTorchbool non_blocking) { auto r_out = lantern__cast_byte_tensor_bool(self.get(), non_blocking.get()); @@ -5137,6 +5123,24 @@ XPtrTorchTensor cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_s return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace__is_all_true_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern__is_all_true_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace__is_any_true_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern__is_any_true_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace__test_check_tensor_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern__test_check_tensor_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_all_self_Tensor_dim_int64_t (XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchbool keepdim) { auto r_out = lantern_all_tensor_intt_bool(self.get(), dim.get(), keepdim.get()); @@ -8117,14 +8121,8 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { - auto r_out = lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { - auto r_out = lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); +XPtrTorchTensor cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { + auto r_out = lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); return XPtrTorchTensor(r_out); } @@ -8339,6 +8337,20 @@ XPtrTorchTensor cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool (XPtrTorchTensor input, XPtrTorchTensor weight0, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor hx_, XPtrTorchTensor cx_, XPtrTorchbool reverse, XPtrTorchIntArrayRef batch_sizes, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool bidirectional, XPtrTorchbool batch_first, XPtrTorchbool train) { + auto r_out = lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(input.get(), weight0.get(), weight1.get(), weight2.get(), weight3.get(), hx_.get(), cx_.get(), reverse.get(), batch_sizes.get(), mode.get(), hidden_size.get(), num_layers.get(), has_biases.get(), bidirectional.get(), batch_first.get(), train.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor (XPtrTorchTensor input, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor weight4, XPtrTorchTensor hx_, XPtrTorchTensor cx_tmp, XPtrTorchTensor output, XPtrTorchTensor hy_, XPtrTorchTensor cy_, XPtrTorchOptionalTensor grad_output, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchbool reverse, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchIntArrayRef batch_sizes, XPtrTorchbool batch_first, XPtrTorchTensor workspace) { + auto r_out = lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(input.get(), weight1.get(), weight2.get(), weight3.get(), weight4.get(), hx_.get(), cx_tmp.get(), output.get(), hy_.get(), cy_.get(), grad_output.get(), grad_hy.get(), grad_cy.get(), reverse.get(), mode.get(), hidden_size.get(), num_layers.get(), has_biases.get(), train.get(), bidirectional.get(), batch_sizes.get(), batch_first.get(), workspace.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 5)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 6))); +} + // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double (XPtrTorchTensor input, XPtrTorchTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchOptionalTensor running_mean, XPtrTorchOptionalTensor running_var, XPtrTorchbool training, XPtrTorchdouble exponential_average_factor, XPtrTorchdouble epsilon) { auto r_out = lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), exponential_average_factor.get(), epsilon.get()); @@ -8416,14 +8428,14 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor (XPtrTorchTensor self, XPtrTorchTensor other) { - auto r_out = lantern__sparse_sparse_matmul_tensor_tensor(self.get(), other.get()); +XPtrTorchTensor cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view (XPtrTorchTensor sparse, XPtrTorchTensor dense, XPtrTorchstring_view reduce) { + auto r_out = lantern__sparse_mm_tensor_tensor_cstringview(sparse.get(), dense.get(), reduce.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor (XPtrTorchTensor t, XPtrTorchTensor mask_indices) { - auto r_out = lantern__sparse_mask_helper_tensor_tensor(t.get(), mask_indices.get()); +XPtrTorchTensor cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor (XPtrTorchTensor self, XPtrTorchTensor other) { + auto r_out = lantern__sparse_sparse_matmul_tensor_tensor(self.get(), other.get()); return XPtrTorchTensor(r_out); } @@ -8553,6 +8565,34 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor out, XPtrTorchTensor save_mean, XPtrTorchTensor save_invstd, XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out.get(), save_mean.get(), save_invstd.get(), input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(input.get(), weight.get(), bias.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor out, XPtrTorchTensor save_mean, XPtrTorchTensor save_invstd, XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out.get(), save_mean.get(), save_invstd.get(), input.get(), weight.get(), bias.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double (XPtrTorchTensor input, XPtrTorchdouble eps) { auto r_out = lantern_batch_norm_stats_tensor_double(input.get(), eps.get()); @@ -9081,6 +9121,12 @@ XPtrTorchTensor cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef (XPtrT return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef size) { + auto r_out = lantern__reshape_copy_tensor_intarrayref(self.get(), size.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride) { auto r_out = lantern__reshape_alias_tensor_intarrayref_intarrayref(self.get(), size.get(), stride.get()); @@ -9172,8 +9218,14 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight) { - auto r_out = lantern_prelu_backward_tensor_tensor_tensor(grad_output.get(), self.get(), weight.get()); +XPtrTorchTensor cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor (XPtrTorchTensor self, XPtrTorchTensor weight) { + auto r_out = lantern__prelu_kernel_tensor_tensor(self.get(), weight.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight) { + auto r_out = lantern__prelu_kernel_backward_tensor_tensor_tensor(grad_output.get(), self.get(), weight.get()); auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } @@ -9640,6 +9692,12 @@ XPtrTorchTensor cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname (XPtrTorchTe return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_squeeze_tensor_intarrayref(self.get(), dim.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor (XPtrTorchTensor self, XPtrTorchTensor mat1, XPtrTorchTensor mat2, XPtrTorchScalar beta, XPtrTorchScalar alpha) { auto r_out = lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar(self.get(), mat1.get(), mat2.get(), beta.get(), alpha.get()); @@ -9832,12 +9890,6 @@ XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef (XPtrTorchTe return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_std_mean_self_Tensor (XPtrTorchTensor self, XPtrTorchbool unbiased) { auto r_out = lantern_std_mean_tensor_bool(self.get(), unbiased.get()); @@ -9852,13 +9904,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_mean_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_std_mean_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); @@ -9866,25 +9911,12 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_mean_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_std_out_tensor_tensor_intarrayref_bool_bool(out.get(), self.get(), dim.get(), unbiased.get(), keepdim.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_out_tensor_tensor_intarrayref_intt_bool(out.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_std_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); @@ -9897,18 +9929,6 @@ XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameLi return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_out_tensor_tensor_dimnamelist_intt_bool(out.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_prod_self_Tensor (XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype) { auto r_out = lantern_prod_tensor_scalartype(self.get(), dtype.get()); @@ -10275,24 +10295,12 @@ XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef (XPtrTorchTe return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_var_out_tensor_tensor_intarrayref_bool_bool(out.get(), self.get(), dim.get(), unbiased.get(), keepdim.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_out_tensor_tensor_intarrayref_intt_bool(out.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_var_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); @@ -10305,18 +10313,6 @@ XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameLi return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_out_tensor_tensor_dimnamelist_intt_bool(out.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_var_mean_self_Tensor (XPtrTorchTensor self, XPtrTorchbool unbiased) { auto r_out = lantern_var_mean_tensor_bool(self.get(), unbiased.get()); @@ -10331,13 +10327,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_mean_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_var_mean_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); @@ -10345,13 +10334,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_mean_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor (XPtrTorchTensor condition, XPtrTorchTensor self, XPtrTorchTensor other) { auto r_out = lantern_where_tensor_tensor_tensor(condition.get(), self.get(), other.get()); @@ -10669,12 +10651,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_frobenius_norm_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern_frobenius_norm_tensor(self.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim, XPtrTorchbool keepdim) { auto r_out = lantern_frobenius_norm_tensor_intarrayref_bool(self.get(), dim.get(), keepdim.get()); @@ -10819,6 +10795,20 @@ XPtrTorchTensor cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view (XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchstring_view reduce) { + auto r_out = lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(self.get(), other.get(), reduce.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2 (XPtrTorchTensor self, XPtrTorchTensor grad_out, XPtrTorchTensor weight, XPtrTorchstring_view reduce, XPtrTorchTensor arg_out, std::vector output_mask) { + auto r_out = lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(self.get(), grad_out.get(), weight.get(), reduce.get(), arg_out.get(), reinterpret_cast(&output_mask)); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor mat1, XPtrTorchTensor mat2, XPtrTorchScalar beta, XPtrTorchScalar alpha) { auto r_out = lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out.get(), self.get(), mat1.get(), mat2.get(), beta.get(), alpha.get()); @@ -11048,8 +11038,8 @@ return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor (XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups) { - auto r_out = lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self.get(), padding.get(), stride.get(), dilation.get(), groups.get()); +XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor (XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups, XPtrTorchOptionalIntArrayRef input_size) { + auto r_out = lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(self.get(), padding.get(), stride.get(), dilation.get(), groups.get(), input_size.get()); return XPtrTorchTensor(r_out); } @@ -11341,12 +11331,12 @@ return XPtrTorchScalar(r_out); Rcpp::List cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { auto r_out = lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4))); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 5))); } // [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { - auto r_out = lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y.get(), grad_hy.get(), grad_cy.get(), z_state.get(), cell_state_fwd.get(), input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); +Rcpp::List cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensor layersOutputs, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { + auto r_out = lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y.get(), grad_hy.get(), grad_cy.get(), z_state.get(), cell_state_fwd.get(), input.get(), layersOutputs.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 2))); } @@ -11958,12 +11948,6 @@ XPtrTorchTensor cpp_torch_namespace_diag_self_Tensor (XPtrTorchTensor self, XPtr return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t (XPtrTorchTensor grad, XPtrTorchIntArrayRef input_sizes, XPtrTorchint64_t diagonal) { - auto r_out = lantern_diag_backward_tensor_intarrayref_intt(grad.get(), input_sizes.get(), diagonal.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchoptional_index_int64_t dim) { auto r_out = lantern_cross_out_tensor_tensor_tensor_intt(out.get(), self.get(), other.get(), dim.get()); @@ -12487,27 +12471,6 @@ XPtrTorchTensor cpp_torch_namespace_linalg_vander_x_Tensor (XPtrTorchTensor x, X return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor (XPtrTorchTensor e, XPtrTorchTensor V, XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern_symeig_out_tensor_tensor_tensor_bool_bool(e.get(), V.get(), self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_symeig_self_Tensor (XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern_symeig_tensor_bool_bool(self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool (XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern__symeig_helper_tensor_bool_bool(self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor (XPtrTorchTensor U, XPtrTorchTensor S, XPtrTorchTensor V, XPtrTorchTensor self, XPtrTorchbool some, XPtrTorchbool compute_uv) { auto r_out = lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(U.get(), S.get(), V.get(), self.get(), some.get(), compute_uv.get()); @@ -13052,6 +13015,12 @@ XPtrTorchTensor cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_max_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_max_out_tensor_tensor(out.get(), self.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_minimum_self_Tensor_other_Tensor (XPtrTorchTensor self, XPtrTorchTensor other) { auto r_out = lantern_minimum_tensor_tensor(self.get(), other.get()); @@ -13435,6 +13404,50 @@ void cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar (XPtrTorchT lantern__foreach_div__tensorlist_scalar(self.get(), scalar.get()); } +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + auto r_out = lantern__foreach_clamp_min_tensorlist_scalar(self.get(), scalar.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_clamp_min__tensorlist_scalar(self.get(), scalar.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + auto r_out = lantern__foreach_clamp_max_tensorlist_scalar(self.get(), scalar.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_clamp_max__tensorlist_scalar(self.get(), scalar.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + auto r_out = lantern__foreach_maximum_tensorlist_scalar(self.get(), scalar.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_maximum__tensorlist_scalar(self.get(), scalar.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + auto r_out = lantern__foreach_minimum_tensorlist_scalar(self.get(), scalar.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_minimum__tensorlist_scalar(self.get(), scalar.get()); +} + // [[Rcpp::export]] XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other, XPtrTorchScalar alpha) { auto r_out = lantern__foreach_add_tensorlist_tensorlist_scalar(self.get(), other.get(), alpha.get()); @@ -13480,52 +13493,140 @@ void cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList (XPtrTor } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - auto r_out = lantern__foreach_add_tensorlist_arrayrefscalar(self.get(), scalars.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + auto r_out = lantern__foreach_clamp_min_tensorlist_tensorlist(self.get(), other.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_add__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - lantern__foreach_add__tensorlist_arrayrefscalar(self.get(), scalars.get()); +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_clamp_min__tensorlist_tensorlist(self.get(), other.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_sub_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - auto r_out = lantern__foreach_sub_tensorlist_arrayrefscalar(self.get(), scalars.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + auto r_out = lantern__foreach_clamp_max_tensorlist_tensorlist(self.get(), other.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_sub__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - lantern__foreach_sub__tensorlist_arrayrefscalar(self.get(), scalars.get()); +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_clamp_max__tensorlist_tensorlist(self.get(), other.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_div_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - auto r_out = lantern__foreach_div_tensorlist_arrayrefscalar(self.get(), scalars.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + auto r_out = lantern__foreach_maximum_tensorlist_tensorlist(self.get(), other.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_div__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - lantern__foreach_div__tensorlist_arrayrefscalar(self.get(), scalars.get()); +void cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_maximum__tensorlist_tensorlist(self.get(), other.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_mul_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - auto r_out = lantern__foreach_mul_tensorlist_arrayrefscalar(self.get(), scalars.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + auto r_out = lantern__foreach_minimum_tensorlist_tensorlist(self.get(), other.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - lantern__foreach_mul__tensorlist_arrayrefscalar(self.get(), scalars.get()); +void cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_minimum__tensorlist_tensorlist(self.get(), other.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_exp_self_TensorList (XPtrTorchTensorList self) { - auto r_out = lantern__foreach_exp_tensorlist(self.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_add_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_add__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_add__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_sub_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_sub_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_sub__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_sub__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_div_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_div_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_div__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_div__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_mul_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_mul_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_mul__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_clamp_min_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_clamp_min__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_clamp_max_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_clamp_max__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_maximum_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_maximum__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_minimum_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_minimum__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_exp_self_TensorList (XPtrTorchTensorList self) { + auto r_out = lantern__foreach_exp_tensorlist(self.get()); return XPtrTorchTensorList(r_out); } @@ -13851,11 +13952,21 @@ void cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_te lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(self.get(), tensor1.get(), tensor2.get(), scalars.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(self.get(), tensor1.get(), tensor2.get(), scalars.get()); +} + // [[Rcpp::export]] void cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars) { lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(self.get(), tensor1.get(), tensor2.get(), scalars.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(self.get(), tensor1.get(), tensor2.get(), scalars.get()); +} + // [[Rcpp::export]] XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchScalar value) { auto r_out = lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(self.get(), tensor1.get(), tensor2.get(), value.get()); @@ -13874,6 +13985,12 @@ XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1 return XPtrTorchTensorList(r_out); } +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + auto r_out = lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(self.get(), tensor1.get(), tensor2.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + // [[Rcpp::export]] XPtrTorchTensorList cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars) { auto r_out = lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(self.get(), tensor1.get(), tensor2.get(), scalars.get()); @@ -13881,33 +13998,39 @@ return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { - auto r_out = lantern__foreach_maximum_tensorlist_tensorlist(self.get(), other.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + auto r_out = lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(self.get(), tensor1.get(), tensor2.get(), scalars.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { - lantern__foreach_maximum__tensorlist_tensorlist(self.get(), other.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_norm_self_TensorList (XPtrTorchTensorList self, XPtrTorchScalar ord) { + auto r_out = lantern__foreach_norm_tensorlist_scalar(self.get(), ord.get()); +return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { - auto r_out = lantern__foreach_minimum_tensorlist_tensorlist(self.get(), other.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights) { + auto r_out = lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(self.get(), tensors1.get(), weights.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { - lantern__foreach_minimum__tensorlist_tensorlist(self.get(), other.get()); +void cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights) { + lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(self.get(), tensors1.get(), weights.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_norm_self_TensorList (XPtrTorchTensorList self, XPtrTorchScalar ord) { - auto r_out = lantern__foreach_norm_tensorlist_scalar(self.get(), ord.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar (XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight) { + auto r_out = lantern__foreach_lerp_tensorlist_tensorlist_scalar(self.get(), tensors1.get(), weight.get()); return XPtrTorchTensorList(r_out); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar (XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight) { + lantern__foreach_lerp__tensorlist_tensorlist_scalar(self.get(), tensors1.get(), weight.get()); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor (XPtrTorchTensor self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right) { auto r_out = lantern_bucketize_tensor_tensor_bool_bool(self.get(), boundaries.get(), out_int32.get(), right.get()); @@ -13932,12 +14055,6 @@ XPtrTorchTensor cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Ten return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern__torch_cuda_cu_linker_symbol_op_tensor(self.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor sorted_sequence, XPtrTorchTensor self, XPtrTorchbool out_int32, XPtrTorchbool right, XPtrTorchoptional_string_view side, XPtrTorchOptionalTensor sorter) { auto r_out = lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(out.get(), sorted_sequence.get(), self.get(), out_int32.get(), right.get(), side.get(), sorter.get()); @@ -14978,72 +15095,36 @@ XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_I return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(input.get(), output_size.get(), scale_factors.get()); @@ -15056,18 +15137,6 @@ XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_outpu return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(input.get(), output_size.get(), scale_factors.get()); @@ -15080,18 +15149,6 @@ XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_outpu return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(input.get(), output_size.get(), scale_factors.get()); @@ -15104,18 +15161,6 @@ XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_outpu return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionaldouble scales) { auto r_out = lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(out.get(), self.get(), output_size.get(), align_corners.get(), scales.get()); @@ -17270,6 +17315,12 @@ XPtrTorchTensor cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t (XPtrTo return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_squeeze_copy_tensor_intarrayref(self.get(), dim.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_t_copy_self_Tensor (XPtrTorchTensor self) { auto r_out = lantern_t_copy_tensor(self.get()); @@ -17342,6 +17393,21 @@ XPtrTorchTensorList cpp_torch_namespace_unbind_copy_self_Tensor (XPtrTorchTensor return XPtrTorchTensorList(r_out); } +// [[Rcpp::export]] +void cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { + lantern_unbind_copy_out_tensorlist_tensor_intt(out.get(), self.get(), dim.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchint64_t split_size, XPtrTorchindex_int64_t dim) { + lantern_split_copy_out_tensorlist_tensor_intt_intt(out.get(), self.get(), split_size.get(), dim.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchIntArrayRef split_sizes, XPtrTorchindex_int64_t dim) { + lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out.get(), self.get(), split_sizes.get(), dim.get()); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef size) { auto r_out = lantern_view_copy_tensor_intarrayref(self.get(), size.get()); @@ -17367,249 +17433,121 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t level) { - auto r_out = lantern__fw_primal_copy_out_tensor_tensor_intt(out.get(), self.get(), level.get()); +XPtrTorchTensor cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor (XPtrTorchTensor self, XPtrTorchTensor query) { + auto r_out = lantern__nested_tensor_softmax_with_shape_tensor_tensor(self.get(), query.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t (XPtrTorchTensor out, XPtrTorchTensor primal, XPtrTorchTensor tangent, XPtrTorchint64_t level) { - auto r_out = lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out.get(), primal.get(), tangent.get(), level.get()); +XPtrTorchTensor cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor (XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchoptional_int64_t mask_type) { + auto r_out = lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(src.get(), embed_dim.get(), num_heads.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), use_gelu.get(), norm_first.get(), eps.get(), norm_weight_1.get(), norm_bias_1.get(), norm_weight_2.get(), norm_bias_2.get(), ffn_weight_1.get(), ffn_bias_1.get(), ffn_weight_2.get(), ffn_bias_2.get(), mask.get(), mask_type.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_view_as_real_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_head, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchOptionalTensor mask, XPtrTorchbool need_weights, XPtrTorchbool average_attn_weights, XPtrTorchoptional_int64_t mask_type) { + auto r_out = lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(query.get(), key.get(), value.get(), embed_dim.get(), num_head.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), mask.get(), need_weights.get(), average_attn_weights.get(), mask_type.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_view_as_complex_copy_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal) { + auto r_out = lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), is_causal.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__conj_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal) { + auto r_out = lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), need_attn_weights.get(), is_causal.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__neg_view_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); +XPtrTorchint64_t cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal) { + auto r_out = lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), is_causal.get()); +return XPtrTorchint64_t(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride, XPtrTorchoptional_int64_t storage_offset) { - auto r_out = lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out.get(), self.get(), size.get(), stride.get(), storage_offset.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchOptionalTensor dropout_mask) { + auto r_out = lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), is_causal.get(), dropout_mask.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size) { - auto r_out = lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), size.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchbool return_debug_mask) { + auto r_out = lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), dropout_p.get(), is_causal.get(), return_debug_mask.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 4)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 5)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 6)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 7)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 8))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t offset, XPtrTorchindex_int64_t dim1, XPtrTorchindex_int64_t dim2) { - auto r_out = lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out.get(), self.get(), offset.get(), dim1.get(), dim2.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t (XPtrTorchTensor grad_out, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchint64_t philox_seed, XPtrTorchint64_t philox_offset) { + auto r_out = lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out.get(), query.get(), key.get(), value.get(), out.get(), logsumexp.get(), cum_seq_q.get(), cum_seq_k.get(), max_q.get(), max_k.get(), dropout_p.get(), is_causal.get(), philox_seed.get(), philox_offset.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchbool implicit) { - auto r_out = lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out.get(), self.get(), size.get(), implicit.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchbool compute_log_sumexp, XPtrTorchbool is_causal) { + auto r_out = lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(query.get(), key.get(), value.get(), compute_log_sumexp.get(), is_causal.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dims) { - auto r_out = lantern_permute_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), dims.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor (XPtrTorchTensor grad_out_, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchbool is_causal, XPtrTorchbool chunk_grad_outputs) { + auto r_out = lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_.get(), query.get(), key.get(), value.get(), out.get(), logsumexp.get(), is_causal.get(), chunk_grad_outputs.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride) { - auto r_out = lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out.get(), self.get(), size.get(), stride.get()); -return XPtrTorchTensor(r_out); +XPtrTorchbool cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchbool is_causal) { + auto r_out = lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(query.get(), key.get(), value.get(), is_causal.get()); +return XPtrTorchbool(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index) { - auto r_out = lantern_select_copy_out_tensor_tensor_intt_intt(out.get(), self.get(), dim.get(), index.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchbool return_debug_mask) { + auto r_out = lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(query.get(), key.get(), value.get(), cum_seq_q.get(), cum_seq_k.get(), max_q.get(), max_k.get(), dropout_p.get(), is_causal.get(), return_debug_mask.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 2)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_detach_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t (XPtrTorchTensor grad_out, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchint64_t philox_seed, XPtrTorchint64_t philox_offset) { + auto r_out = lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out.get(), query.get(), key.get(), value.get(), out.get(), logsumexp.get(), cum_seq_q.get(), cum_seq_k.get(), max_q.get(), max_k.get(), dropout_p.get(), is_causal.get(), philox_seed.get(), philox_offset.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchoptional_int64_t start, XPtrTorchoptional_int64_t end, XPtrTorchint64_t step) { - auto r_out = lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out.get(), self.get(), dim.get(), start.get(), end.get(), step.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor cu_seqlens_q, XPtrTorchOptionalTensor cu_seqlens_k, XPtrTorchoptional_int64_t max_seqlen_q, XPtrTorchbool compute_log_sumexp, XPtrTorchbool causal) { + auto r_out = lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(query.get(), key.get(), value.get(), cu_seqlens_q.get(), cu_seqlens_k.get(), max_seqlen_q.get(), compute_log_sumexp.get(), causal.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -void cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchint64_t split_size, XPtrTorchindex_int64_t dim) { - lantern_split_copy_out_tensorlist_tensor_intt_intt(out.get(), self.get(), split_size.get(), dim.get()); +Rcpp::List cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor (XPtrTorchTensor grad_out_, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchbool is_causal, XPtrTorchbool chunk_grad_outputs) { + auto r_out = lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_.get(), query.get(), key.get(), value.get(), out.get(), logsumexp.get(), is_causal.get(), chunk_grad_outputs.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } // [[Rcpp::export]] -void cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchIntArrayRef split_sizes, XPtrTorchindex_int64_t dim) { - lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out.get(), self.get(), split_sizes.get(), dim.get()); +XPtrTorchTensor cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor (XPtrTorchTensor q, XPtrTorchTensor k, XPtrTorchTensor v, XPtrTorchdouble dropout_p) { + auto r_out = lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(q.get(), k.get(), v.get(), dropout_p.get()); +return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_squeeze_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { - auto r_out = lantern_squeeze_copy_out_tensor_tensor_intt(out.get(), self.get(), dim.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_t_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim0, XPtrTorchindex_int64_t dim1) { - auto r_out = lantern_transpose_copy_out_tensor_tensor_intt_intt(out.get(), self.get(), dim0.get(), dim1.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { - auto r_out = lantern_unsqueeze_copy_out_tensor_tensor_intt(out.get(), self.get(), dim.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__indices_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__values_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_indices_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_values_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_crow_indices_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_col_indices_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -void cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { - lantern_unbind_copy_out_tensorlist_tensor_intt(out.get(), self.get(), dim.get()); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size) { - auto r_out = lantern_view_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), size.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDtype dtype) { - auto r_out = lantern_view_copy_out_tensor_tensor_scalartype(out.get(), self.get(), dtype.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step) { - auto r_out = lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out.get(), self.get(), dimension.get(), size.get(), step.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_alias_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor (XPtrTorchTensor self, XPtrTorchTensor query) { - auto r_out = lantern__nested_tensor_softmax_with_shape_tensor_tensor(self.get(), query.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor (XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchoptional_int64_t mask_type) { - auto r_out = lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(src.get(), embed_dim.get(), num_heads.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), use_gelu.get(), norm_first.get(), eps.get(), norm_weight_1.get(), norm_bias_1.get(), norm_weight_2.get(), norm_bias_2.get(), ffn_weight_1.get(), ffn_bias_1.get(), ffn_weight_2.get(), ffn_bias_2.get(), mask.get(), mask_type.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_head, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchOptionalTensor mask, XPtrTorchbool need_weights, XPtrTorchbool average_attn_weights, XPtrTorchoptional_int64_t mask_type) { - auto r_out = lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(query.get(), key.get(), value.get(), embed_dim.get(), num_head.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), mask.get(), need_weights.get(), average_attn_weights.get(), mask_type.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal) { - auto r_out = lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), need_attn_weights.get(), is_causal.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal) { - auto r_out = lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), need_attn_weights.get(), is_causal.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal) { - auto r_out = lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), need_attn_weights.get(), is_causal.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor (XPtrTorchTensor q, XPtrTorchTensor k, XPtrTorchTensor v, XPtrTorchdouble dropout_p) { - auto r_out = lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(q.get(), k.get(), v.get(), dropout_p.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_head, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchOptionalTensor mask) { - auto r_out = lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor(query.get(), key.get(), value.get(), embed_dim.get(), num_head.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), mask.get()); +XPtrTorchTensor cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_head, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchOptionalTensor mask) { + auto r_out = lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor(query.get(), key.get(), value.get(), embed_dim.get(), num_head.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), mask.get()); return XPtrTorchTensor(r_out); } @@ -17625,12 +17563,6 @@ XPtrTorchTensor cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor (XPt return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal) { - auto r_out = lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(query.get(), key.get(), value.get(), cum_seq_q.get(), cum_seq_k.get(), max_q.get(), max_k.get(), dropout_p.get(), is_causal.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor (XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchOptionalTensor incr_key, XPtrTorchOptionalTensor incr_value) { auto r_out = lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(src.get(), embed_dim.get(), num_heads.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), use_gelu.get(), norm_first.get(), eps.get(), norm_weight_1.get(), norm_bias_1.get(), norm_weight_2.get(), norm_bias_2.get(), ffn_weight_1.get(), ffn_bias_1.get(), ffn_weight_2.get(), ffn_bias_2.get(), mask.get(), incr_key.get(), incr_value.get()); @@ -18220,6 +18152,11 @@ void cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_ lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self.get(), grads.get(), exp_avgs.get(), exp_avg_sqs.get(), max_exp_avg_sqs.get(), state_steps.get(), lr.get(), beta1.get(), beta2.get(), weight_decay.get(), eps.get(), amsgrad.get(), maximize.get(), grad_scale.get(), found_inf.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool (XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf) { + lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self.get(), grads.get(), exp_avgs.get(), exp_avg_sqs.get(), max_exp_avg_sqs.get(), state_steps.get(), lr.get(), beta1.get(), beta2.get(), weight_decay.get(), eps.get(), amsgrad.get(), maximize.get(), grad_scale.get(), found_inf.get()); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchint64_t self_num_batch_dims) { auto r_out = lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(out.get(), self.get(), other.get(), self_num_batch_dims.get()); @@ -18530,6 +18467,13 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor log_probs, XPtrTorchTensor targets, XPtrTorchTensor input_lengths, XPtrTorchTensor target_lengths, XPtrTorchint64_t blank, XPtrTorchbool zero_infinity) { + auto r_out = lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(out0.get(), out1.get(), log_probs.get(), targets.get(), input_lengths.get(), target_lengths.get(), blank.get(), zero_infinity.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t (XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor log_probs, XPtrTorchTensor targets, XPtrTorchIntArrayRef input_lengths, XPtrTorchIntArrayRef target_lengths, XPtrTorchTensor neg_log_likelihood, XPtrTorchTensor log_alpha, XPtrTorchint64_t blank, XPtrTorchbool zero_infinity) { auto r_out = lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(out.get(), grad.get(), log_probs.get(), targets.get(), input_lengths.get(), target_lengths.get(), neg_log_likelihood.get(), log_alpha.get(), blank.get(), zero_infinity.get()); @@ -18923,14 +18867,8 @@ return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPt } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { - auto r_out = lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { - auto r_out = lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out.get(), grad_output.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); +XPtrTorchTensor cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { + auto r_out = lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out.get(), grad_output.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); return XPtrTorchTensor(r_out); } @@ -19001,6 +18939,20 @@ XPtrTorchTensor cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tenso return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor input, XPtrTorchTensor weight0, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor hx_, XPtrTorchTensor cx_, XPtrTorchbool reverse, XPtrTorchIntArrayRef batch_sizes, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool bidirectional, XPtrTorchbool batch_first, XPtrTorchbool train) { + auto r_out = lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(out0.get(), out1.get(), out2.get(), out3.get(), input.get(), weight0.get(), weight1.get(), weight2.get(), weight3.get(), hx_.get(), cx_.get(), reverse.get(), batch_sizes.get(), mode.get(), hidden_size.get(), num_layers.get(), has_biases.get(), bidirectional.get(), batch_first.get(), train.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor out5, XPtrTorchTensor out6, XPtrTorchTensor input, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor weight4, XPtrTorchTensor hx_, XPtrTorchTensor cx_tmp, XPtrTorchTensor output, XPtrTorchTensor hy_, XPtrTorchTensor cy_, XPtrTorchOptionalTensor grad_output, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchbool reverse, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchIntArrayRef batch_sizes, XPtrTorchbool batch_first, XPtrTorchTensor workspace) { + auto r_out = lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(out0.get(), out1.get(), out2.get(), out3.get(), out4.get(), out5.get(), out6.get(), input.get(), weight1.get(), weight2.get(), weight3.get(), weight4.get(), hx_.get(), cx_tmp.get(), output.get(), hy_.get(), cy_.get(), grad_output.get(), grad_hy.get(), grad_cy.get(), reverse.get(), mode.get(), hidden_size.get(), num_layers.get(), has_biases.get(), train.get(), bidirectional.get(), batch_sizes.get(), batch_first.get(), workspace.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 5)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 6))); +} + // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor input, XPtrTorchTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchOptionalTensor running_mean, XPtrTorchOptionalTensor running_var, XPtrTorchbool training, XPtrTorchdouble exponential_average_factor, XPtrTorchdouble epsilon) { auto r_out = lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out0.get(), out1.get(), out2.get(), input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), exponential_average_factor.get(), epsilon.get()); @@ -19052,15 +19004,16 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor (XPtrTorchTensor out, XPtrTorchTensor t, XPtrTorchTensor mask_indices) { - auto r_out = lantern__sparse_mask_helper_out_tensor_tensor_tensor(out.get(), t.get(), mask_indices.get()); +XPtrTorchTensor cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchScalar other) { + auto r_out = lantern_mul_out_tensor_tensor_scalar(out.get(), self.get(), other.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchScalar other) { - auto r_out = lantern_mul_out_tensor_tensor_scalar(out.get(), self.get(), other.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4))); } // [[Rcpp::export]] @@ -19261,19 +19214,6 @@ XPtrTorchTensor cpp_torch_namespace_relu_out_out_Tensor_self_Tensor (XPtrTorchTe return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight) { - auto r_out = lantern_prelu_out_tensor_tensor_tensor(out.get(), self.get(), weight.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight) { - auto r_out = lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(out0.get(), out1.get(), grad_output.get(), self.get(), weight.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchIntArrayRef input_sizes, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index) { auto r_out = lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(out.get(), grad_output.get(), input_sizes.get(), dim.get(), index.get()); @@ -19332,13 +19272,6 @@ XPtrTorchTensor cpp_torch_namespace_sum_out_out_Tensor_self_Tensor (XPtrTorchTen return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_mean_out_tensor_tensor_tensor_intarrayref_intt_bool(out0.get(), out1.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_prod_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype) { auto r_out = lantern_prod_out_tensor_tensor_scalartype(out.get(), self.get(), dtype.get()); @@ -19459,13 +19392,6 @@ XPtrTorchTensor cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_mean_out_tensor_tensor_tensor_intarrayref_intt_bool(out0.get(), out1.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor v, XPtrTorchTensor g, XPtrTorchindex_int64_t dim) { auto r_out = lantern__weight_norm_interface_out_tensor_tensor_tensor_tensor_intt(out0.get(), out1.get(), v.get(), g.get(), dim.get()); @@ -19769,32 +19695,32 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_to_sparse_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchLayout layout, XPtrTorchOptionalIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(out.get(), self.get(), layout.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_to_sparse_csr_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_csr_out_tensor_tensor_intt(out.get(), self.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_to_sparse_csc_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_csc_out_tensor_tensor_intt(out.get(), self.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize) { - auto r_out = lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(out.get(), self.get(), blocksize.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(out.get(), self.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize) { - auto r_out = lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(out.get(), self.get(), blocksize.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(out.get(), self.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } @@ -19805,8 +19731,8 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups) { - auto r_out = lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out.get(), self.get(), padding.get(), stride.get(), dilation.get(), groups.get()); +XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups, XPtrTorchOptionalIntArrayRef input_size) { + auto r_out = lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(out.get(), self.get(), padding.get(), stride.get(), dilation.get(), groups.get(), input_size.get()); return XPtrTorchTensor(r_out); } @@ -19940,15 +19866,15 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { - auto r_out = lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0.get(), out1.get(), out2.get(), out3.get(), out4.get(), input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); +Rcpp::List cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor out5, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { + auto r_out = lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0.get(), out1.get(), out2.get(), out3.get(), out4.get(), out5.get(), input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4))); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 5))); } // [[Rcpp::export]] -void cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor out0, XPtrTorchTensorList out1, XPtrTorchTensorList out2, XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { - lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0.get(), out1.get(), out2.get(), grad_y.get(), grad_hy.get(), grad_cy.get(), z_state.get(), cell_state_fwd.get(), input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); +void cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor out0, XPtrTorchTensorList out1, XPtrTorchTensorList out2, XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensor layersOutputs, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { + lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0.get(), out1.get(), out2.get(), grad_y.get(), grad_hy.get(), grad_cy.get(), z_state.get(), cell_state_fwd.get(), input.get(), layersOutputs.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); } // [[Rcpp::export]] @@ -20262,13 +20188,6 @@ XPtrTorchTensor cpp_torch_namespace_trace_out_out_Tensor_self_Tensor (XPtrTorchT return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(out0.get(), out1.get(), self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor A, XPtrTorchbool upper) { auto r_out = lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(out.get(), self.get(), A.get(), upper.get()); @@ -20367,6 +20286,26 @@ void cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_ lantern__foreach_div_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); +} + // [[Rcpp::export]] void cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other, XPtrTorchScalar alpha) { lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(out.get(), self.get(), other.get(), alpha.get()); @@ -20387,6 +20326,26 @@ void cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_T lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +} + // [[Rcpp::export]] void cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); @@ -20407,6 +20366,26 @@ void cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); +} + // [[Rcpp::export]] void cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self) { lantern__foreach_exp_out_tensorlist_tensorlist(out.get(), self.get()); @@ -20574,18 +20553,18 @@ void cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_ten } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars) { - lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), tensor1.get(), tensor2.get(), scalars.get()); +void cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out.get(), self.get(), tensor1.get(), tensor2.get(), scalars.get()); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { - lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars) { + lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), tensor1.get(), tensor2.get(), scalars.get()); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { - lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out.get(), self.get(), tensor1.get(), tensor2.get(), scalars.get()); } // [[Rcpp::export]] @@ -20594,14 +20573,18 @@ void cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList (XPtrT } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor (XPtrTorchTensor out, XPtrTorchScalar self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right) { - auto r_out = lantern_bucketize_out_tensor_scalar_tensor_bool_bool(out.get(), self.get(), boundaries.get(), out_int32.get(), right.get()); -return XPtrTorchTensor(r_out); +void cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights) { + lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(out.get(), self.get(), tensors1.get(), weights.get()); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(out.get(), self.get()); +void cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight) { + lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(out.get(), self.get(), tensors1.get(), weight.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor (XPtrTorchTensor out, XPtrTorchScalar self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right) { + auto r_out = lantern_bucketize_out_tensor_scalar_tensor_bool_bool(out.get(), self.get(), boundaries.get(), out_int32.get(), right.get()); return XPtrTorchTensor(r_out); } @@ -20666,237 +20649,255 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +Rcpp::List cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, std::vector output_mask) { + auto r_out = lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(out0.get(), out1.get(), out2.get(), grad_output.get(), self.get(), weight.get(), kernel_size.get(), stride.get(), padding.get(), reinterpret_cast(&output_mask)); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { + auto r_out = lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { + auto r_out = lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { + auto r_out = lantern_slow_conv_dilated3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_isinf_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_linalg_matrix_exp_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends) { + auto r_out = lantern__test_optional_intlist_out_tensor_tensor_intarrayref(out.get(), values.get(), addends.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends) { + auto r_out = lantern__test_optional_filled_intlist_out_tensor_tensor_intarrayref(out.get(), values.get(), addends.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalDoubleArrayRef addends) { + auto r_out = lantern__test_optional_floatlist_out_tensor_tensor_arrayrefdouble(out.get(), values.get(), addends.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__test_warn_in_autograd_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__test_autograd_multiple_dispatch_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__test_autograd_multiple_dispatch_view_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view (XPtrTorchTensor out, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchIndexTensor indices, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchbool unsafe, XPtrTorchoptional_scalar initial) { + auto r_out = lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar(out.get(), data.get(), reduce.get(), lengths.get(), indices.get(), offsets.get(), axis.get(), unsafe.get(), initial.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view (XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor output, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchoptional_scalar initial) { + auto r_out = lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(out.get(), grad.get(), output.get(), data.get(), reduce.get(), lengths.get(), offsets.get(), axis.get(), initial.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList (XPtrTorchTensor out, XPtrTorchTensorList list, XPtrTorchoptional_scalar_type dtype, XPtrTorchLayout layout, XPtrTorchDevice device, XPtrTorchoptional_bool pin_memory) { + auto r_out = lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(out.get(), list.get(), dtype.get(), layout.get(), device.get(), pin_memory.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t level) { + auto r_out = lantern__fw_primal_copy_out_tensor_tensor_intt(out.get(), self.get(), level.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t (XPtrTorchTensor out, XPtrTorchTensor primal, XPtrTorchTensor tangent, XPtrTorchint64_t level) { + auto r_out = lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out.get(), primal.get(), tangent.get(), level.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_view_as_real_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_view_as_complex_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__conj_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__neg_view_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride, XPtrTorchoptional_int64_t storage_offset) { + auto r_out = lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out.get(), self.get(), size.get(), stride.get(), storage_offset.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size) { + auto r_out = lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), size.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t offset, XPtrTorchindex_int64_t dim1, XPtrTorchindex_int64_t dim2) { + auto r_out = lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out.get(), self.get(), offset.get(), dim1.get(), dim2.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchbool implicit) { + auto r_out = lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out.get(), self.get(), size.get(), implicit.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, std::vector output_mask) { - auto r_out = lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(out0.get(), out1.get(), out2.get(), grad_output.get(), self.get(), weight.get(), kernel_size.get(), stride.get(), padding.get(), reinterpret_cast(&output_mask)); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +XPtrTorchTensor cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dims) { + auto r_out = lantern_permute_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), dims.get()); +return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { - auto r_out = lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); +XPtrTorchTensor cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride) { + auto r_out = lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out.get(), self.get(), size.get(), stride.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { - auto r_out = lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); +XPtrTorchTensor cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index) { + auto r_out = lantern_select_copy_out_tensor_tensor_intt_intt(out.get(), self.get(), dim.get(), index.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { - auto r_out = lantern_slow_conv_dilated3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); +XPtrTorchTensor cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_detach_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_isinf_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchoptional_int64_t start, XPtrTorchoptional_int64_t end, XPtrTorchint64_t step) { + auto r_out = lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out.get(), self.get(), dim.get(), start.get(), end.get(), step.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_linalg_matrix_exp_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_squeeze_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends) { - auto r_out = lantern__test_optional_intlist_out_tensor_tensor_intarrayref(out.get(), values.get(), addends.get()); +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { + auto r_out = lantern_squeeze_copy_out_tensor_tensor_intt(out.get(), self.get(), dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends) { - auto r_out = lantern__test_optional_filled_intlist_out_tensor_tensor_intarrayref(out.get(), values.get(), addends.get()); +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_squeeze_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalDoubleArrayRef addends) { - auto r_out = lantern__test_optional_floatlist_out_tensor_tensor_arrayrefdouble(out.get(), values.get(), addends.get()); +XPtrTorchTensor cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_t_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__test_warn_in_autograd_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim0, XPtrTorchindex_int64_t dim1) { + auto r_out = lantern_transpose_copy_out_tensor_tensor_intt_intt(out.get(), self.get(), dim0.get(), dim1.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__test_autograd_multiple_dispatch_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { + auto r_out = lantern_unsqueeze_copy_out_tensor_tensor_intt(out.get(), self.get(), dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__test_autograd_multiple_dispatch_view_copy_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__indices_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view (XPtrTorchTensor out, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchIndexTensor indices, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchbool unsafe, XPtrTorchoptional_scalar initial) { - auto r_out = lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar(out.get(), data.get(), reduce.get(), lengths.get(), indices.get(), offsets.get(), axis.get(), unsafe.get(), initial.get()); +XPtrTorchTensor cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__values_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view (XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor output, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchoptional_scalar initial) { - auto r_out = lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(out.get(), grad.get(), output.get(), data.get(), reduce.get(), lengths.get(), offsets.get(), axis.get(), initial.get()); +XPtrTorchTensor cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_indices_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList (XPtrTorchTensor out, XPtrTorchTensorList list, XPtrTorchoptional_scalar_type dtype, XPtrTorchLayout layout, XPtrTorchDevice device, XPtrTorchoptional_bool pin_memory) { - auto r_out = lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(out.get(), list.get(), dtype.get(), layout.get(), device.get(), pin_memory.get()); +XPtrTorchTensor cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_values_copy_out_tensor_tensor(out.get(), self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_crow_indices_copy_out_tensor_tensor(out.get(), self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_col_indices_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } @@ -20913,14 +20914,32 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchdouble padding, XPtrTorchOptionalIntArrayRef output_size) { - auto r_out = lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(out.get(), self.get(), padding.get(), output_size.get()); +XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size) { + auto r_out = lantern_view_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), size.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchdouble eps) { - auto r_out = lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(out.get(), self.get(), weight.get(), bias.get(), eps.get()); +XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDtype dtype) { + auto r_out = lantern_view_copy_out_tensor_tensor_scalartype(out.get(), self.get(), dtype.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step) { + auto r_out = lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out.get(), self.get(), dimension.get(), size.get(), step.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_alias_copy_out_tensor_tensor(out.get(), self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchdouble padding, XPtrTorchOptionalIntArrayRef output_size) { + auto r_out = lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(out.get(), self.get(), padding.get(), output_size.get()); return XPtrTorchTensor(r_out); } @@ -20981,3 +21000,15 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensorList(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 4))); } +// [[Rcpp::export]] +void cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf) { + lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out.get(), self.get(), grads.get(), exp_avgs.get(), exp_avg_sqs.get(), max_exp_avg_sqs.get(), state_steps.get(), lr.get(), beta1.get(), beta2.get(), weight_decay.get(), eps.get(), amsgrad.get(), maximize.get(), grad_scale.get(), found_inf.get()); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool (XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf) { + auto r_out = lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self.get(), grads.get(), exp_avgs.get(), exp_avg_sqs.get(), max_exp_avg_sqs.get(), state_steps.get(), lr.get(), beta1.get(), beta2.get(), weight_decay.get(), eps.get(), amsgrad.get(), maximize.get(), grad_scale.get(), found_inf.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensorList(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 4))); +} + diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index 759e9b4cbb..2af1f269c9 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -1,7 +1,7 @@ cmake_minimum_required(VERSION 3.19.2) project(lantern) -set(TORCH_VERSION "1.13.1") +set(TORCH_VERSION "2.0.1") if (NOT DEFINED TORCH_PATH) if (DEFINED ENV{TORCH_PATH}) diff --git a/src/lantern/headers/declarations/declarations.yaml b/src/lantern/headers/declarations/declarations.yaml index 30d70db719..88688e1499 100644 --- a/src/lantern/headers/declarations/declarations.yaml +++ b/src/lantern/headers/declarations/declarations.yaml @@ -6150,6 +6150,113 @@ with_gil: false deprecated: false has_math_kernel: true +- name: _is_all_true + operator_name: _is_all_true + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_is_all_true(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _is_any_true + operator_name: _is_any_true + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_is_any_true(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_check_tensor + operator_name: _test_check_tensor + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_check_tensor(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true - name: all operator_name: all overload_name: dim @@ -10177,11 +10284,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: bilinear operator_name: bilinear overload_name: '' @@ -11999,7 +12106,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::broadcast_to(Tensor(a) self, int[] size) -> Tensor(a) + schema_string: aten::broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -13072,7 +13179,7 @@ type: ::std::vector inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: false with_gil: false deprecated: false @@ -13082,7 +13189,7 @@ overload_name: sections manual_kernel_registration: false category_override: '' - schema_string: aten::tensor_split.sections(Tensor(a -> *) self, int sections, int dim=0) -> Tensor(a)[] + schema_string: aten::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -13140,7 +13247,7 @@ overload_name: indices manual_kernel_registration: false category_override: '' - schema_string: aten::tensor_split.indices(Tensor(a -> *) self, int[] indices, int dim=0) -> Tensor(a)[] + schema_string: aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -14875,7 +14982,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::constant_pad_nd(Tensor self, int[] pad, Scalar value=0) -> Tensor + schema_string: aten::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -14981,7 +15088,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor + schema_string: aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -15096,7 +15203,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) + schema_string: aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -15486,7 +15593,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor + schema_string: aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -15881,7 +15988,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) + schema_string: aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -17272,11 +17379,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: copy_ operator_name: copy_ overload_name: '' @@ -24191,7 +24298,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor + schema_string: aten::embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -24272,7 +24379,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor + schema_string: aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -24357,7 +24464,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor + schema_string: aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25234,7 +25341,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25381,7 +25488,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25508,7 +25615,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -31728,7 +31835,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_fft_c2c(Tensor self, int[] dim, int normalization, bool forward) -> Tensor + schema_string: aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -31793,7 +31900,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_fft_c2c.out(Tensor self, int[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -34412,7 +34519,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::layer_norm(Tensor input, int[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor + schema_string: aten::layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -39598,7 +39705,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, int[] sizes, bool keepdim) -> Tensor + schema_string: aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, SymInt[] sizes, bool keepdim) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40106,17 +40213,128 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: true -- name: _mps_max_pool2d - operator_name: _mps_max_pool2d +- name: max_pool2d_backward + operator_name: max_pool2d_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: ceil_mode + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: ceil_mode + type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_max_pool2d + operator_name: mkldnn_max_pool2d overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_mps_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40212,12 +40430,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mps_max_pool2d_backward - operator_name: mps_max_pool2d_backward +- name: mkldnn_max_pool2d_backward + operator_name: mkldnn_max_pool2d_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mps_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40227,7 +40445,12 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef @@ -40262,7 +40485,7 @@ is_nullable: false name: ceil_mode type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -40272,7 +40495,12 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef @@ -40323,12 +40551,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mkldnn_max_pool2d - operator_name: mkldnn_max_pool2d +- name: mkldnn_max_pool3d + operator_name: mkldnn_max_pool3d overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40339,28 +40567,28 @@ dynamic_type: at::IntArrayRef is_nullable: false name: kernel_size - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: '{}' dynamic_type: at::IntArrayRef is_nullable: false name: stride - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 0 dynamic_type: at::IntArrayRef is_nullable: false name: padding - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 1 dynamic_type: at::IntArrayRef is_nullable: false name: dilation - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: false @@ -40379,250 +40607,28 @@ dynamic_type: at::IntArrayRef is_nullable: false name: kernel_size - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: '{}' dynamic_type: at::IntArrayRef is_nullable: false name: stride - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 0 dynamic_type: at::IntArrayRef is_nullable: false name: padding - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 1 dynamic_type: at::IntArrayRef is_nullable: false name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_max_pool2d_backward - operator_name: mkldnn_max_pool2d_backward - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_max_pool3d - operator_name: mkldnn_max_pool3d - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 + size: 3 type: at::IntArrayRef - annotation: null default: false @@ -42969,7 +42975,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups) -> Tensor + schema_string: aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43059,12 +43065,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: miopen_batch_norm - operator_name: miopen_batch_norm +- name: mkldnn_rnn_layer + operator_name: mkldnn_rnn_layer overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) + schema_string: aten::mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -43074,39 +43080,506 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: weight + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + name: result3 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_backward + operator_name: mkldnn_rnn_layer_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer_backward(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: bias + name: grad_output type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: running_mean + name: grad_hy type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: running_var + name: grad_cy type: const c10::optional & - annotation: null dynamic_type: bool is_nullable: false - name: training + name: reverse type: bool - annotation: null - dynamic_type: double + dynamic_type: int64_t is_nullable: false - name: exponential_average_factor - type: double + name: mode + type: int64_t - annotation: null - dynamic_type: double + dynamic_type: int64_t is_nullable: false - name: epsilon - type: double - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double) + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + name: result3 + type: at::Tensor + - dynamic_type: at::Tensor + name: result4 + type: at::Tensor + - dynamic_type: at::Tensor + name: result5 + type: at::Tensor + - dynamic_type: at::Tensor + name: result6 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: miopen_batch_norm + operator_name: miopen_batch_norm + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: running_mean + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: running_var + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: exponential_average_factor + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: epsilon + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -43286,7 +43759,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43401,7 +43874,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43526,7 +43999,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -44417,312 +44890,53 @@ with_gil: false deprecated: false has_math_kernel: true -- name: _sparse_sparse_matmul - operator_name: _sparse_sparse_matmul - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _sparse_mask_helper - operator_name: _sparse_mask_helper - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_sparse_mask_helper(Tensor t, Tensor mask_indices) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: t - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: mask_indices - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: t - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: mask_indices - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode - operator_name: mode - overload_name: '' +- name: _sparse_mm + operator_name: _sparse_mm + overload_name: reduce manual_kernel_registration: false category_override: '' - schema_string: aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) + schema_string: aten::_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self + name: sparse type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode_out - operator_name: mode - overload_name: values - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: dense type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool + dynamic_type: c10::string_view is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + name: reduce + type: c10::string_view + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode - operator_name: mode - overload_name: dimname - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self + name: sparse type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: dense type: const at::Tensor & - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool + dynamic_type: c10::string_view is_nullable: false - name: keepdim - type: bool + name: reduce + type: c10::string_view method_of: - Type - - Tensor - namespace mode: native - python_module: '' + python_module: sparse returns: - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor - - dynamic_type: at::Tensor - field_name: indices - name: indices + name: result type: at::Tensor inplace: false is_factory_method: false @@ -44731,106 +44945,375 @@ with_gil: false deprecated: false has_math_kernel: true -- name: mode_out - operator_name: mode - overload_name: dimname_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: mul - operator_name: mul - overload_name: Tensor +- name: _sparse_sparse_matmul + operator_name: _sparse_sparse_matmul + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mul.Tensor(Tensor self, Tensor other) -> Tensor + schema_string: aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode + operator_name: mode + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode_out + operator_name: mode + overload_name: values + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode + operator_name: mode + overload_name: dimname + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: mode_out + operator_name: mode + overload_name: dimname_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: mul + operator_name: mul + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::mul.Tensor(Tensor self, Tensor other) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -45712,7 +46195,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::narrow(Tensor(a) self, int dim, int start, int length) -> Tensor(a) + schema_string: aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -45778,7 +46261,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, int length) -> Tensor(a) + schema_string: aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -46103,6 +46586,494 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _native_batch_norm_legit + operator_name: _native_batch_norm_legit + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, at::Tensor &, at::Tensor &, bool, double, double) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit_out + operator_name: _native_batch_norm_legit + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!), Tensor(e!), Tensor(f!)) + arguments: + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, at::Tensor &, at::Tensor &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_mean + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_invstd + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit + operator_name: _native_batch_norm_legit + overload_name: no_stats + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, bool, double, double) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit_out + operator_name: _native_batch_norm_legit + overload_name: no_stats_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.no_stats_out(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_mean + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_invstd + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: batch_norm_stats operator_name: batch_norm_stats overload_name: '' @@ -47024,7 +47995,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, int[2] padding, int[2] stride=1) -> Tensor + schema_string: aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, int[2] stride=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -49165,7 +50136,7 @@ overload_name: names manual_kernel_registration: false category_override: '' - schema_string: aten::rand.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49247,7 +50218,7 @@ overload_name: generator_with_names manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_with_names(int[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49341,7 +50312,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::rand(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49411,7 +50382,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator(int[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49493,7 +50464,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -49542,7 +50513,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_out(int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -49687,7 +50658,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::randint(int high, int[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49767,7 +50738,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::randint.generator(int high, int[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49859,7 +50830,7 @@ overload_name: low manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low(int low, int high, int[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49949,7 +50920,7 @@ overload_name: low_generator manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_generator(int low, int high, int[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -50051,7 +51022,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.out(int high, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50110,7 +51081,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.generator_out(int high, int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50181,7 +51152,7 @@ overload_name: low_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_out(int low, int high, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50250,7 +51221,7 @@ overload_name: low_generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_generator_out(int low, int high, int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50529,7 +51500,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::randn(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50599,7 +51570,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator(int[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50681,7 +51652,7 @@ overload_name: names manual_kernel_registration: false category_override: '' - schema_string: aten::randn.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50763,7 +51734,7 @@ overload_name: generator_with_names manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_with_names(int[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50857,7 +51828,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50906,7 +51877,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_out(int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -52180,7 +53151,7 @@ overload_name: self_int manual_kernel_registration: false category_override: '' - schema_string: aten::repeat_interleave.self_int(Tensor self, int repeats, int? dim=None, *, int? output_size=None) -> Tensor + schema_string: aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, int? output_size=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -52293,6 +53264,51 @@ with_gil: false deprecated: false has_math_kernel: true +- name: _reshape_copy + operator_name: _reshape_copy + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_reshape_copy(Tensor self, SymInt[] size) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: _reshape_alias operator_name: _reshape_alias overload_name: '' @@ -53066,17 +54082,62 @@ type: at::Tensor inplace: false is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: _prelu_kernel + operator_name: _prelu_kernel + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_prelu_kernel(Tensor self, Tensor weight) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: prelu_backward - operator_name: prelu_backward +- name: _prelu_kernel_backward + operator_name: _prelu_kernel_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::prelu_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) + schema_string: aten::_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -53112,7 +54173,6 @@ type: const at::Tensor & method_of: - Type - - Tensor - namespace mode: native python_module: '' @@ -53884,7 +54944,7 @@ overload_name: int manual_kernel_registration: false category_override: '' - schema_string: aten::select.int(Tensor(a) self, int dim, int index) -> Tensor(a) + schema_string: aten::select.int(Tensor(a) self, int dim, SymInt index) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -53940,7 +55000,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, int index) -> Tensor + schema_string: aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -54005,7 +55065,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, int index) -> Tensor + schema_string: aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -55688,7 +56748,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_scatter(Tensor self, Tensor src, int dim, int index) -> Tensor + schema_string: aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -56417,7 +57477,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split.Tensor(Tensor self, int split_size, int dim=0) -> Tensor[] + schema_string: aten::unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -56475,7 +57535,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::split.Tensor(Tensor(a -> *) self, int split_size, int dim=0) -> Tensor(a)[] + schema_string: aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -56533,7 +57593,7 @@ overload_name: sizes manual_kernel_registration: false category_override: '' - schema_string: aten::split.sizes(Tensor(a -> *) self, int[] split_size, int dim=0) -> Tensor(a)[] + schema_string: aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -56591,7 +57651,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split_with_sizes(Tensor self, int[] split_sizes, int dim=0) -> Tensor[] + schema_string: aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -56649,7 +57709,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::split_with_sizes(Tensor(a -> *) self, int[] split_sizes, int dim=0) -> Tensor(a)[] + schema_string: aten::split_with_sizes(Tensor(a -> *) self, SymInt[] split_sizes, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -57106,6 +58166,52 @@ with_gil: false deprecated: false has_math_kernel: true +- name: squeeze + operator_name: squeeze + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a) + arguments: + - annotation: a + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: a + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: squeeze_ operator_name: squeeze_ overload_name: '' @@ -57186,6 +58292,51 @@ with_gil: false deprecated: false has_math_kernel: false +- name: squeeze_ + operator_name: squeeze_ + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!) + arguments: + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: self + type: at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: self + type: at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - Tensor + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: self + type: at::Tensor & + inplace: true + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: squeeze_ operator_name: squeeze_ overload_name: dimname @@ -59391,7 +60542,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::std.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -59399,12 +60550,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59425,12 +60578,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59589,7 +60744,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::std_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -59597,12 +60752,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59623,12 +60780,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59739,7 +60898,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::std_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -59753,6 +60912,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59779,6 +60939,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59900,7 +61061,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::std.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -59915,12 +61076,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59941,12 +61104,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60144,7 +61309,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::std.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -60158,6 +61323,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60184,6 +61350,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60218,7 +61385,7 @@ overload_name: correction_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -60239,6 +61406,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60265,6 +61433,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64030,7 +65199,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::var.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -64038,12 +65207,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64064,12 +65235,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64189,7 +65362,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::var.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -64204,12 +65377,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64230,12 +65405,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64433,7 +65610,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -64447,6 +65624,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64473,6 +65651,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64507,7 +65686,7 @@ overload_name: correction_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -64528,6 +65707,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64554,6 +65734,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64718,7 +65899,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::var_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -64726,12 +65907,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64752,12 +65935,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64868,7 +66053,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -64882,6 +66067,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64908,6 +66094,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -65205,6 +66392,7 @@ type: const at::Scalar & method_of: - Type + - Tensor - namespace mode: native python_module: '' @@ -68219,23 +69407,47 @@ has_math_kernel: false - name: frobenius_norm operator_name: frobenius_norm - overload_name: '' + overload_name: dim manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm(Tensor self) -> Tensor + schema_string: aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + size: 1 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + size: 1 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool method_of: - Type - namespace @@ -68252,13 +69464,20 @@ with_gil: false deprecated: false has_math_kernel: true -- name: frobenius_norm +- name: frobenius_norm_out operator_name: frobenius_norm - overload_name: dim + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor + schema_string: aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -68276,7 +69495,7 @@ is_nullable: false name: keepdim type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, bool) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -68295,6 +69514,60 @@ is_nullable: false name: keepdim type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: nuclear_norm + operator_name: nuclear_norm + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool method_of: - Type - namespace @@ -68311,12 +69584,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: frobenius_norm_out - operator_name: frobenius_norm +- name: nuclear_norm_out + operator_name: nuclear_norm overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -68330,133 +69603,13 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dim - size: 1 - type: at::IntArrayRef - annotation: null default: false dynamic_type: bool is_nullable: false name: keepdim type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dim - size: 1 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: nuclear_norm - operator_name: nuclear_norm - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: nuclear_norm_out - operator_name: nuclear_norm - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, bool, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -69995,20 +71148,30 @@ with_gil: false deprecated: false has_math_kernel: false -- name: addmm_out - operator_name: addmm - overload_name: out +- name: _sparse_mm_reduce_impl + operator_name: _sparse_mm_reduce_impl + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_mm_reduce_impl(Tensor self, Tensor other, str reduce) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, c10::string_view) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -70017,28 +71180,164 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: mat1 + name: other + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + method_of: + - Type + - namespace + mode: native + python_module: sparse + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _sparse_mm_reduce_impl_backward + operator_name: _sparse_mm_reduce_impl_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: mat2 + name: grad_out type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor is_nullable: false - kwarg_only: true - name: beta - type: const at::Scalar & + name: weight + type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: c10::string_view is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &) + name: reduce + type: c10::string_view + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: arg_out + type: const at::Tensor & + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const at::Tensor &, ::std::array) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: arg_out + type: const at::Tensor & + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + method_of: + - Type + - namespace + mode: native + python_module: sparse + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: addmm_out + operator_name: addmm + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: mat1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: mat2 + type: const at::Tensor & + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: beta + type: const at::Scalar & + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -72152,7 +73451,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -72703,7 +74002,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, int[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor + schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -74066,20 +75365,64 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse(Tensor self) -> Tensor + schema_string: aten::to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional, at::OptionalIntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74101,20 +75444,32 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csr(Tensor self) -> Tensor + schema_string: aten::to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74136,20 +75491,32 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csc(Tensor self) -> Tensor + schema_string: aten::to_sparse_csc(Tensor self, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74171,7 +75538,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsr(Tensor self, int[2] blocksize) -> Tensor + schema_string: aten::to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74184,7 +75551,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74197,6 +75570,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74218,7 +75597,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsc(Tensor self, int[2] blocksize) -> Tensor + schema_string: aten::to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74231,7 +75610,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74244,6 +75629,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74312,7 +75703,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_reorder_conv2d_weight(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1) -> Tensor + schema_string: aten::mkldnn_reorder_conv2d_weight(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, int[]? input_size=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74346,7 +75737,13 @@ is_nullable: false name: groups type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t) + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::OptionalIntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74380,6 +75777,12 @@ is_nullable: false name: groups type: int64_t + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef method_of: - Type - namespace @@ -77882,7 +79285,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_lstm_mps(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor, Tensor, Tensor) + schema_string: aten::_lstm_mps(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -77929,7 +79332,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -77997,6 +79400,9 @@ - dynamic_type: at::Tensor name: result4 type: at::Tensor + - dynamic_type: at::Tensor + name: result5 + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -78009,7 +79415,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::lstm_mps_backward(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[]) + schema_string: aten::lstm_mps_backward(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[]) arguments: - annotation: null dynamic_type: at::Tensor @@ -78041,6 +79447,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -78081,7 +79492,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple,::std::vector> (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) + schema_order_cpp_signature: ::std::tuple,::std::vector> (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -78113,6 +79524,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -80846,7 +82262,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pack_padded_sequence_backward(Tensor grad, int[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor + schema_string: aten::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -88647,180 +90063,125 @@ type: at::Tensor & inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: diag - operator_name: diag - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::diag(Tensor self, int diagonal=0) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: diag_backward - operator_name: diag_backward - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::diag_backward(Tensor grad, SymInt[] input_sizes, int diagonal) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_sizes - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_sizes - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: true -- name: cross_out - operator_name: cross - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: diag + operator_name: diag + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::diag(Tensor self, int diagonal=0) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: diagonal + type: int64_t + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: diagonal + type: int64_t + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: cross_out + operator_name: cross + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false abstract: false device_guard: true with_gil: false @@ -89327,7 +90688,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::trace_backward(Tensor grad, int[] sizes) -> Tensor + schema_string: aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -93066,7 +94427,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::index_select_backward(Tensor grad, int[] self_sizes, int dim, Tensor index) -> Tensor + schema_string: aten::index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -94338,7 +95699,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, float label_smoothing=0.0) -> Tensor + schema_string: aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, float label_smoothing=0.0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -94918,190 +96279,55 @@ with_gil: false deprecated: false has_math_kernel: true -- name: symeig_out - operator_name: symeig - overload_name: e +- name: svd_out + operator_name: svd + overload_name: U manual_kernel_registration: false category_override: '' - schema_string: aten::symeig.e(Tensor self, bool eigenvectors=False, bool upper=True, *, Tensor(a!) e, Tensor(b!) V) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) + schema_string: aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor - field_name: eigenvalues + field_name: U is_nullable: false - name: e + name: U output: true type: at::Tensor & - allocate: true annotation: b! dynamic_type: at::Tensor - field_name: eigenvectors - is_nullable: false - name: V - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: upper - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: eigenvalues + field_name: S is_nullable: false - name: e + name: S output: true type: at::Tensor & - allocate: true - annotation: b! + annotation: c! dynamic_type: at::Tensor - field_name: eigenvectors + field_name: V is_nullable: false name: V output: true type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: eigenvalues - name: e - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: eigenvectors - name: V - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: symeig - operator_name: symeig - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::symeig(Tensor self, bool eigenvectors=False, bool upper=True) -> (Tensor eigenvalues, Tensor eigenvectors) - arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - annotation: null default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors + name: some type: bool - annotation: null default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: eigenvalues - name: eigenvalues - type: at::Tensor - - dynamic_type: at::Tensor - field_name: eigenvectors - name: eigenvectors_return - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _symeig_helper - operator_name: _symeig_helper - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_symeig_helper(Tensor self, bool eigenvectors, bool upper) -> (Tensor, Tensor) - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper + name: compute_uv type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -95109,100 +96335,16 @@ name: self type: const at::Tensor & - annotation: null + default: true dynamic_type: bool is_nullable: false - name: eigenvectors + name: some type: bool - annotation: null + default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result0 - type: at::Tensor - - dynamic_type: at::Tensor - name: result1 - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: svd_out - operator_name: svd - overload_name: U - manual_kernel_registration: false - category_override: '' - schema_string: aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: U - is_nullable: false - name: U - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: S - is_nullable: false - name: S - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - field_name: V - is_nullable: false - name: V - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: some - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: compute_uv - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: some - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: compute_uv + name: compute_uv type: bool - allocate: true annotation: a! @@ -101246,45 +102388,48 @@ with_gil: false deprecated: false has_math_kernel: true -- name: minimum - operator_name: minimum - overload_name: '' +- name: max_out + operator_name: max + overload_name: unary_out manual_kernel_registration: false category_override: '' - schema_string: aten::minimum(Tensor self, Tensor other) -> Tensor + schema_string: aten::max.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - - annotation: null + - allocate: true + annotation: a! dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & + name: out + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: other + name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null + - allocate: true + annotation: a! dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Tensor & + name: out + output: true + type: at::Tensor & method_of: - Type - - Tensor - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: result - type: at::Tensor + name: out + type: at::Tensor & inplace: false is_factory_method: false abstract: true @@ -101292,20 +102437,13 @@ with_gil: false deprecated: false has_math_kernel: false -- name: minimum_out +- name: minimum operator_name: minimum - overload_name: out + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::minimum(Tensor self, Tensor other) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -101316,7 +102454,7 @@ is_nullable: false name: other type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101328,22 +102466,16 @@ is_nullable: false name: other type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type + - Tensor - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -101351,12 +102483,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: min_out - operator_name: min +- name: minimum_out + operator_name: minimum overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101405,147 +102537,17 @@ type: at::Tensor & inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true -- name: min + has_math_kernel: false +- name: min_out operator_name: min - overload_name: other - manual_kernel_registration: false - category_override: '' - schema_string: aten::min.other(Tensor self, Tensor other) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: quantile - operator_name: quantile - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: q - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: q - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: quantile_out - operator_name: quantile overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101562,28 +102564,9 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: q + name: other type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101593,27 +102576,8 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: q + name: other type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - allocate: true annotation: a! dynamic_type: at::Tensor @@ -101637,12 +102601,58 @@ with_gil: false deprecated: false has_math_kernel: true +- name: min + operator_name: min + overload_name: other + manual_kernel_registration: false + category_override: '' + schema_string: aten::min.other(Tensor self, Tensor other) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true - name: quantile operator_name: quantile - overload_name: scalar + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -101650,10 +102660,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101673,7 +102683,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101681,10 +102691,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101723,10 +102733,10 @@ has_math_kernel: true - name: quantile_out operator_name: quantile - overload_name: scalar_out + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101741,10 +102751,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101764,7 +102774,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101772,10 +102782,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101818,12 +102828,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: nanquantile - operator_name: nanquantile - overload_name: '' +- name: quantile + operator_name: quantile + overload_name: scalar manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -101831,10 +102841,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101854,7 +102864,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101862,10 +102872,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101902,12 +102912,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: nanquantile_out - operator_name: nanquantile - overload_name: out +- name: quantile_out + operator_name: quantile + overload_name: scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101922,10 +102932,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101945,7 +102955,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101953,10 +102963,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102001,10 +103011,10 @@ has_math_kernel: true - name: nanquantile operator_name: nanquantile - overload_name: scalar + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -102012,10 +103022,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102035,7 +103045,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102043,10 +103053,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102085,10 +103095,10 @@ has_math_kernel: true - name: nanquantile_out operator_name: nanquantile - overload_name: scalar_out + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -102103,10 +103113,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102126,7 +103136,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102134,10 +103144,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102180,27 +103190,102 @@ with_gil: false deprecated: false has_math_kernel: true -- name: sort_out - operator_name: sort - overload_name: values +- name: nanquantile + operator_name: nanquantile + overload_name: scalar manual_kernel_registration: false category_override: '' - schema_string: aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + schema_string: aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor - field_name: values is_nullable: false - name: values - output: true - type: at::Tensor & + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: double + is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: double + is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: nanquantile_out + operator_name: nanquantile + overload_name: scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + arguments: - allocate: true - annotation: b! + annotation: a! dynamic_type: at::Tensor - field_name: indices is_nullable: false - name: indices + name: out output: true type: at::Tensor & - annotation: null @@ -102209,18 +103294,30 @@ name: self type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t + dynamic_type: double is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true name: dim - type: int64_t + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: descending + name: keepdim type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102228,31 +103325,34 @@ name: self type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t + dynamic_type: double is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true name: dim - type: int64_t + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: descending + name: keepdim type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view is_nullable: false - name: values - output: true - type: at::Tensor & + kwarg_only: true + name: interpolation + type: c10::string_view - allocate: true - annotation: b! + annotation: a! dynamic_type: at::Tensor - field_name: indices is_nullable: false - name: indices + name: out output: true type: at::Tensor & method_of: @@ -102262,26 +103362,117 @@ python_module: '' returns: - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices + name: out type: at::Tensor & inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: sort_out operator_name: sort - overload_name: values_stable + overload_name: values manual_kernel_registration: false category_override: '' - schema_string: aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + schema_string: aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: descending + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: descending + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: sort_out + operator_name: sort + overload_name: values_stable + manual_kernel_registration: false + category_override: '' + schema_string: aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) arguments: - allocate: true annotation: a! @@ -103814,7 +105005,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::unfold_backward(Tensor grad_in, int[] input_sizes, int dim, int size, int step) -> Tensor + schema_string: aten::unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -105289,7 +106480,7 @@ overload_name: float_float manual_kernel_registration: false category_override: '' - schema_string: aten::normal.float_float(float mean, float std, int[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::normal.float_float(float mean, float std, SymInt[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: double @@ -105393,7 +106584,7 @@ overload_name: float_float_out manual_kernel_registration: false category_override: '' - schema_string: aten::normal.float_float_out(float mean, float std, int[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::normal.float_float_out(float mean, float std, SymInt[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -105992,48 +107183,121 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add - operator_name: _foreach_add - overload_name: List +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + schema_string: aten::_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type @@ -106051,12 +107315,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_ - operator_name: _foreach_add_ - overload_name: List +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + schema_string: aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106064,91 +107328,150 @@ name: self type: at::TensorList - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) - schema_order_arguments: - - annotation: a! + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_maximum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type - namespace mode: native python_module: '' - returns: [] - inplace: true + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub - operator_name: _foreach_sub - overload_name: List +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + schema_string: aten::_foreach_maximum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) - schema_order_arguments: + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type @@ -106166,18 +107489,60 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_ - operator_name: _foreach_sub_ - overload_name: List +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + schema_string: aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add + operator_name: _foreach_add + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -106190,9 +107555,68 @@ kwarg_only: true name: alpha type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: a! + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add_ + operator_name: _foreach_add_ + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -106222,12 +107646,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul - operator_name: _foreach_mul +- name: _foreach_sub + operator_name: _foreach_sub overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106239,7 +107663,14 @@ is_nullable: false name: other type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106251,6 +107682,13 @@ is_nullable: false name: other type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & method_of: - Type - namespace @@ -106267,12 +107705,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_ - operator_name: _foreach_mul_ +- name: _foreach_sub_ + operator_name: _foreach_sub_ overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106284,7 +107722,14 @@ is_nullable: false name: other type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106296,6 +107741,13 @@ is_nullable: false name: other type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & method_of: - Type - namespace @@ -106309,12 +107761,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div - operator_name: _foreach_div +- name: _foreach_mul + operator_name: _foreach_mul overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106354,12 +107806,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_ - operator_name: _foreach_div_ +- name: _foreach_mul_ + operator_name: _foreach_mul_ overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106396,12 +107848,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add - operator_name: _foreach_add - overload_name: ScalarList +- name: _foreach_div + operator_name: _foreach_div + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106409,11 +107861,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106421,10 +107873,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106441,12 +107893,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_ - operator_name: _foreach_add_ - overload_name: ScalarList +- name: _foreach_div_ + operator_name: _foreach_div_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106454,11 +107906,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106466,10 +107918,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106483,12 +107935,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub - operator_name: _foreach_sub - overload_name: ScalarList +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106496,11 +107948,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106508,10 +107960,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106528,12 +107980,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_ - operator_name: _foreach_sub_ - overload_name: ScalarList +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106541,11 +107993,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106553,10 +108005,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106570,12 +108022,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div - operator_name: _foreach_div - overload_name: ScalarList +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106583,11 +108035,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106595,10 +108047,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106615,12 +108067,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_ - operator_name: _foreach_div_ - overload_name: ScalarList +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106628,11 +108080,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106640,10 +108092,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106657,12 +108109,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul - operator_name: _foreach_mul - overload_name: ScalarList +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106670,11 +108122,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106682,10 +108134,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106702,12 +108154,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_ - operator_name: _foreach_mul_ - overload_name: ScalarList +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106715,11 +108167,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106727,10 +108179,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106744,25 +108196,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_exp - operator_name: _foreach_exp - overload_name: '' +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_exp(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList method_of: - Type - namespace @@ -106779,56 +108241,34 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_zero_ - operator_name: _foreach_zero_ - overload_name: '' +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_zero_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false - name: self + name: other type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_exp_ - operator_name: _foreach_exp_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_exp_(Tensor(a!)[] self) -> () - arguments: + schema_order_cpp_signature: void (at::TensorList, at::TensorList) + schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false - name: self + name: other type: at::TensorList method_of: - Type @@ -106843,25 +108283,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sqrt - operator_name: _foreach_sqrt - overload_name: '' +- name: _foreach_add + operator_name: _foreach_add + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sqrt(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106878,25 +108328,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sqrt_ - operator_name: _foreach_sqrt_ - overload_name: '' +- name: _foreach_add_ + operator_name: _foreach_add_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sqrt_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106910,25 +108370,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_abs - operator_name: _foreach_abs - overload_name: '' +- name: _foreach_sub + operator_name: _foreach_sub + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_abs(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106945,25 +108415,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_abs_ - operator_name: _foreach_abs_ - overload_name: '' +- name: _foreach_sub_ + operator_name: _foreach_sub_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_abs_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106977,25 +108457,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_acos - operator_name: _foreach_acos - overload_name: '' +- name: _foreach_div + operator_name: _foreach_div + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_acos(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107012,25 +108502,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_acos_ - operator_name: _foreach_acos_ - overload_name: '' +- name: _foreach_div_ + operator_name: _foreach_div_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_acos_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107044,25 +108544,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_asin - operator_name: _foreach_asin - overload_name: '' +- name: _foreach_mul + operator_name: _foreach_mul + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_asin(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107079,25 +108589,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_asin_ - operator_name: _foreach_asin_ - overload_name: '' +- name: _foreach_mul_ + operator_name: _foreach_mul_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_asin_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107111,25 +108631,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_atan - operator_name: _foreach_atan - overload_name: '' +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_atan(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107146,25 +108676,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_atan_ - operator_name: _foreach_atan_ - overload_name: '' +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_atan_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107178,25 +108718,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_ceil - operator_name: _foreach_ceil - overload_name: '' +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_ceil(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107213,25 +108763,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_ceil_ - operator_name: _foreach_ceil_ - overload_name: '' +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_ceil_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107245,25 +108805,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cos - operator_name: _foreach_cos - overload_name: '' +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cos(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_maximum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107280,25 +108850,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cos_ - operator_name: _foreach_cos_ - overload_name: '' +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cos_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_maximum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107312,25 +108892,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cosh - operator_name: _foreach_cosh - overload_name: '' +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cosh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107347,25 +108937,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cosh_ - operator_name: _foreach_cosh_ - overload_name: '' +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cosh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107379,12 +108979,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erf - operator_name: _foreach_erf +- name: _foreach_exp + operator_name: _foreach_exp overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erf(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_exp(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107414,12 +109014,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erf_ - operator_name: _foreach_erf_ +- name: _foreach_zero_ + operator_name: _foreach_zero_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erf_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_zero_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107446,47 +109046,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erfc - operator_name: _foreach_erfc - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_erfc(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_erfc_ - operator_name: _foreach_erfc_ +- name: _foreach_exp_ + operator_name: _foreach_exp_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erfc_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_exp_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107513,12 +109078,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_expm1 - operator_name: _foreach_expm1 +- name: _foreach_sqrt + operator_name: _foreach_sqrt overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_expm1(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_sqrt(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107548,12 +109113,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_expm1_ - operator_name: _foreach_expm1_ +- name: _foreach_sqrt_ + operator_name: _foreach_sqrt_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_expm1_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_sqrt_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107580,12 +109145,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_floor - operator_name: _foreach_floor +- name: _foreach_abs + operator_name: _foreach_abs overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_floor(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_abs(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107615,12 +109180,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_floor_ - operator_name: _foreach_floor_ +- name: _foreach_abs_ + operator_name: _foreach_abs_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_floor_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_abs_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107647,12 +109212,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log - operator_name: _foreach_log +- name: _foreach_acos + operator_name: _foreach_acos overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_acos(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107682,146 +109247,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log_ - operator_name: _foreach_log_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log_(Tensor(a!)[] self) -> () - arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log10 - operator_name: _foreach_log10 - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log10(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log10_ - operator_name: _foreach_log10_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log10_(Tensor(a!)[] self) -> () - arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log1p - operator_name: _foreach_log1p - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log1p(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log1p_ - operator_name: _foreach_log1p_ +- name: _foreach_acos_ + operator_name: _foreach_acos_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log1p_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_acos_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107848,12 +109279,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log2 - operator_name: _foreach_log2 +- name: _foreach_asin + operator_name: _foreach_asin overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log2(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_asin(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107883,12 +109314,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log2_ - operator_name: _foreach_log2_ +- name: _foreach_asin_ + operator_name: _foreach_asin_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log2_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_asin_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107915,12 +109346,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_neg - operator_name: _foreach_neg +- name: _foreach_atan + operator_name: _foreach_atan overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_neg(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_atan(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107950,12 +109381,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_neg_ - operator_name: _foreach_neg_ +- name: _foreach_atan_ + operator_name: _foreach_atan_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_neg_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_atan_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107982,12 +109413,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tan - operator_name: _foreach_tan +- name: _foreach_ceil + operator_name: _foreach_ceil overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tan(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_ceil(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108017,12 +109448,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tan_ - operator_name: _foreach_tan_ +- name: _foreach_ceil_ + operator_name: _foreach_ceil_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tan_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_ceil_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108049,12 +109480,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tanh - operator_name: _foreach_tanh +- name: _foreach_cos + operator_name: _foreach_cos overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tanh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_cos(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108084,12 +109515,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tanh_ - operator_name: _foreach_tanh_ +- name: _foreach_cos_ + operator_name: _foreach_cos_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tanh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_cos_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108116,12 +109547,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sin - operator_name: _foreach_sin +- name: _foreach_cosh + operator_name: _foreach_cosh overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sin(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_cosh(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108151,12 +109582,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sin_ - operator_name: _foreach_sin_ +- name: _foreach_cosh_ + operator_name: _foreach_cosh_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sin_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_cosh_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108183,12 +109614,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sinh - operator_name: _foreach_sinh +- name: _foreach_erf + operator_name: _foreach_erf overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sinh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_erf(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108218,12 +109649,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sinh_ - operator_name: _foreach_sinh_ +- name: _foreach_erf_ + operator_name: _foreach_erf_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sinh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_erf_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108250,12 +109681,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_round - operator_name: _foreach_round +- name: _foreach_erfc + operator_name: _foreach_erfc overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_round(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_erfc(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108285,12 +109716,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_round_ - operator_name: _foreach_round_ +- name: _foreach_erfc_ + operator_name: _foreach_erfc_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_round_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_erfc_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108317,12 +109748,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_lgamma - operator_name: _foreach_lgamma +- name: _foreach_expm1 + operator_name: _foreach_expm1 overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_lgamma(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_expm1(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108352,12 +109783,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_lgamma_ - operator_name: _foreach_lgamma_ +- name: _foreach_expm1_ + operator_name: _foreach_expm1_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_lgamma_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_expm1_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108384,12 +109815,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_frac - operator_name: _foreach_frac +- name: _foreach_floor + operator_name: _foreach_floor overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_frac(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_floor(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108419,12 +109850,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_frac_ - operator_name: _foreach_frac_ +- name: _foreach_floor_ + operator_name: _foreach_floor_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_frac_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_floor_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108451,12 +109882,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_reciprocal - operator_name: _foreach_reciprocal +- name: _foreach_log + operator_name: _foreach_log overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108486,12 +109917,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_reciprocal_ - operator_name: _foreach_reciprocal_ +- name: _foreach_log_ + operator_name: _foreach_log_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108518,12 +109949,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sigmoid - operator_name: _foreach_sigmoid +- name: _foreach_log10 + operator_name: _foreach_log10 overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log10(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108553,12 +109984,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sigmoid_ - operator_name: _foreach_sigmoid_ +- name: _foreach_log10_ + operator_name: _foreach_log10_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log10_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108585,12 +110016,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_trunc - operator_name: _foreach_trunc +- name: _foreach_log1p + operator_name: _foreach_log1p overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_trunc(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log1p(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108620,12 +110051,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_trunc_ - operator_name: _foreach_trunc_ +- name: _foreach_log1p_ + operator_name: _foreach_log1p_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_trunc_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log1p_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108652,57 +110083,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv_ - operator_name: _foreach_addcdiv_ - overload_name: Scalar +- name: _foreach_log2 + operator_name: _foreach_log2 + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () + schema_string: aten::_foreach_log2(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_log2_ + operator_name: _foreach_log2_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_log2_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_neg + operator_name: _foreach_neg + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_neg(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_neg_ + operator_name: _foreach_neg_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_neg_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tan + operator_name: _foreach_tan + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tan(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tan_ + operator_name: _foreach_tan_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tan_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108716,57 +110284,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul_ - operator_name: _foreach_addcmul_ - overload_name: Scalar +- name: _foreach_tanh + operator_name: _foreach_tanh + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () + schema_string: aten::_foreach_tanh(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tanh_ + operator_name: _foreach_tanh_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tanh_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sin + operator_name: _foreach_sin + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sin(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sin_ + operator_name: _foreach_sin_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sin_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sinh + operator_name: _foreach_sinh + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sinh(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sinh_ + operator_name: _foreach_sinh_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sinh_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108780,55 +110485,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv_ - operator_name: _foreach_addcdiv_ - overload_name: ScalarList +- name: _foreach_round + operator_name: _foreach_round + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () + schema_string: aten::_foreach_round(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_round_ + operator_name: _foreach_round_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_round_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lgamma + operator_name: _foreach_lgamma + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lgamma(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lgamma_ + operator_name: _foreach_lgamma_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lgamma_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_frac + operator_name: _foreach_frac + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_frac(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - dynamic_type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_frac_ + operator_name: _foreach_frac_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_frac_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108842,55 +110686,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul_ - operator_name: _foreach_addcmul_ - overload_name: ScalarList +- name: _foreach_reciprocal + operator_name: _foreach_reciprocal + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () + schema_string: aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_reciprocal_ + operator_name: _foreach_reciprocal_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sigmoid + operator_name: _foreach_sigmoid + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sigmoid_ + operator_name: _foreach_sigmoid_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_trunc + operator_name: _foreach_trunc + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_trunc(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - dynamic_type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_trunc_ + operator_name: _foreach_trunc_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_trunc_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108904,14 +110887,14 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv - operator_name: _foreach_addcdiv +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108932,9 +110915,9 @@ is_nullable: false name: value type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108960,25 +110943,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul - operator_name: _foreach_addcmul +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] + schema_string: aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108999,9 +110979,9 @@ is_nullable: false name: value type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109027,25 +111007,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv - operator_name: _foreach_addcdiv +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109065,9 +111042,9 @@ is_nullable: false name: scalars type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109092,25 +111069,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul - operator_name: _foreach_addcmul - overload_name: ScalarList +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ + overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109126,13 +111100,13 @@ name: tensor2 type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::Tensor is_nullable: false name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109148,34 +111122,31 @@ name: tensor2 type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::Tensor is_nullable: false name: scalars - type: at::ArrayRef + type: const at::Tensor & method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum - operator_name: _foreach_maximum - overload_name: List +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109183,11 +111154,21 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) - schema_order_arguments: - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109195,30 +111176,37 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum_ - operator_name: _foreach_maximum_ - overload_name: List +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ + overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_addcmul_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -109228,9 +111216,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -109240,8 +111238,18 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & method_of: - Type - namespace @@ -109255,12 +111263,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum - operator_name: _foreach_minimum - overload_name: List +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -109270,9 +111278,20 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -109282,8 +111301,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & method_of: - Type - namespace @@ -109300,14 +111330,14 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum_ - operator_name: _foreach_minimum_ - overload_name: List +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self @@ -109315,11 +111345,22 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self @@ -109327,27 +111368,41 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & method_of: - Type - namespace mode: native python_module: '' - returns: [] - inplace: true + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_norm - operator_name: _foreach_norm - overload_name: Scalar +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] + schema_string: aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -109355,12 +111410,21 @@ name: self type: at::TensorList - annotation: null - default: 2 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: ord - type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -109368,11 +111432,20 @@ name: self type: at::TensorList - annotation: null - default: 2 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: ord - type: const at::Scalar & + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -109389,41 +111462,497 @@ with_gil: false deprecated: false has_math_kernel: false -- name: bucketize - operator_name: bucketize +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor + schema_string: aten::_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: self - type: const at::Tensor & + type: at::TensorList - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: boundaries - type: const at::Tensor & + name: tensor1 + type: at::TensorList - annotation: null - default: false - dynamic_type: bool + dynamic_type: at::TensorList is_nullable: false - kwarg_only: true - name: out_int32 - type: bool + name: tensor2 + type: at::TensorList - annotation: null - default: false - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - kwarg_only: true - name: right - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool) + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: ScalarList + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcmul.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_norm + operator_name: _foreach_norm + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp + operator_name: _foreach_lerp + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_ + operator_name: _foreach_lerp_ + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp + operator_name: _foreach_lerp + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_ + operator_name: _foreach_lerp_ + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: bucketize + operator_name: bucketize + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: boundaries + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: out_int32 + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: right + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & @@ -109723,41 +112252,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _torch_cuda_cu_linker_symbol_op - operator_name: _torch_cuda_cu_linker_symbol_op - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_torch_cuda_cu_linker_symbol_op(Tensor self) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false - name: searchsorted_out operator_name: searchsorted overload_name: Tensor_out @@ -111450,7 +113944,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nll_loss.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -111545,7 +114039,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_nd(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss_nd(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -111626,7 +114120,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -111707,7 +114201,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -111813,7 +114307,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight) + schema_string: aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) arguments: - annotation: null dynamic_type: at::Tensor @@ -111893,7 +114387,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112002,7 +114496,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight) -> Tensor + schema_string: aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -112097,7 +114591,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112192,7 +114686,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -112273,7 +114767,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -112379,7 +114873,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight) + schema_string: aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) arguments: - annotation: null dynamic_type: at::Tensor @@ -112459,7 +114953,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112568,7 +115062,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight) -> Tensor + schema_string: aten::nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -116944,7 +119438,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::adaptive_avg_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -117005,7 +119499,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::adaptive_avg_pool3d(Tensor self, int[3] output_size) -> Tensor + schema_string: aten::adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -117052,7 +119546,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_adaptive_avg_pool3d(Tensor self, int[3] output_size) -> Tensor + schema_string: aten::_adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120595,7 +123089,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d.out(Tensor self, int[2] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120656,7 +123150,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d(Tensor self, int[2] padding) -> Tensor + schema_string: aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120703,7 +123197,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, int[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120774,7 +123268,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, int[2] padding) -> Tensor + schema_string: aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120831,7 +123325,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d.out(Tensor self, int[4] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120892,7 +123386,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d(Tensor self, int[4] padding) -> Tensor + schema_string: aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120939,7 +123433,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, int[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121010,7 +123504,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, int[4] padding) -> Tensor + schema_string: aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121067,7 +123561,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d.out(Tensor self, int[6] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121128,7 +123622,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d(Tensor self, int[6] padding) -> Tensor + schema_string: aten::reflection_pad3d(Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121175,7 +123669,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, int[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121246,7 +123740,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d_backward(Tensor grad_output, Tensor self, int[6] padding) -> Tensor + schema_string: aten::reflection_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121303,7 +123797,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d.out(Tensor self, int[2] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121364,7 +123858,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d(Tensor self, int[2] padding) -> Tensor + schema_string: aten::replication_pad1d(Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121411,7 +123905,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, int[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121482,7 +123976,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d_backward(Tensor grad_output, Tensor self, int[2] padding) -> Tensor + schema_string: aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121539,7 +124033,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d.out(Tensor self, int[4] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121600,7 +124094,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d(Tensor self, int[4] padding) -> Tensor + schema_string: aten::replication_pad2d(Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121647,7 +124141,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d_backward.grad_input(Tensor grad_output, Tensor self, int[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121718,7 +124212,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d_backward(Tensor grad_output, Tensor self, int[4] padding) -> Tensor + schema_string: aten::replication_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121775,7 +124269,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d.out(Tensor self, int[6] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121836,7 +124330,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d(Tensor self, int[6] padding) -> Tensor + schema_string: aten::replication_pad3d(Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121883,7 +124377,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, int[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121954,7 +124448,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d_backward(Tensor grad_output, Tensor self, int[6] padding) -> Tensor + schema_string: aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122011,7 +124505,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pad_circular(Tensor self, int[] pad) -> Tensor + schema_string: aten::_pad_circular(Tensor self, SymInt[] pad) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122056,7 +124550,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pad_enum(Tensor self, int[] pad, int mode, float? value=None) -> Tensor + schema_string: aten::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122123,7 +124617,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::pad(Tensor self, int[] pad, str mode="constant", float? value=None) -> Tensor + schema_string: aten::pad(Tensor self, SymInt[] pad, str mode="constant", float? value=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122247,86 +124741,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_linear1d_backward - operator_name: upsample_linear1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_linear1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: upsample_bilinear2d operator_name: upsample_bilinear2d overload_name: vec @@ -122387,33 +124806,28 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bilinear2d_backward - operator_name: upsample_bilinear2d_backward + has_math_kernel: true +- name: _upsample_bilinear2d_aa + operator_name: _upsample_bilinear2d_aa overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122424,23 +124838,18 @@ is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122462,17 +124871,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bilinear2d_aa - operator_name: _upsample_bilinear2d_aa + has_math_kernel: true +- name: upsample_trilinear3d + operator_name: upsample_trilinear3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122527,33 +124936,28 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bilinear2d_aa_backward - operator_name: _upsample_bilinear2d_aa_backward + has_math_kernel: true +- name: upsample_bicubic2d + operator_name: upsample_bicubic2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122564,23 +124968,18 @@ is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122602,17 +125001,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_trilinear3d - operator_name: upsample_trilinear3d + has_math_kernel: true +- name: _upsample_bicubic2d_aa + operator_name: _upsample_bicubic2d_aa overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122667,65 +125066,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_trilinear3d_backward - operator_name: upsample_trilinear3d_backward + has_math_kernel: true +- name: upsample_nearest1d + operator_name: upsample_nearest1d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122742,17 +125121,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bicubic2d - operator_name: upsample_bicubic2d + has_math_kernel: true +- name: _upsample_nearest_exact1d + operator_name: _upsample_nearest_exact1d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122764,17 +125143,12 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -122786,11 +125160,6 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122807,65 +125176,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bicubic2d_backward - operator_name: upsample_bicubic2d_backward + has_math_kernel: true +- name: upsample_nearest2d + operator_name: upsample_nearest2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122882,17 +125231,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bicubic2d_aa - operator_name: _upsample_bicubic2d_aa + has_math_kernel: true +- name: _upsample_nearest_exact2d + operator_name: _upsample_nearest_exact2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122904,17 +125253,12 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -122926,11 +125270,6 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122947,65 +125286,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bicubic2d_aa_backward - operator_name: _upsample_bicubic2d_aa_backward + has_math_kernel: true +- name: upsample_nearest3d + operator_name: upsample_nearest3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -123022,17 +125341,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_nearest1d - operator_name: upsample_nearest1d + has_math_kernel: true +- name: _upsample_nearest_exact3d + operator_name: _upsample_nearest_exact3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -123077,676 +125396,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact1d - operator_name: _upsample_nearest_exact1d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest1d_backward - operator_name: upsample_nearest1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact1d_backward - operator_name: _upsample_nearest_exact1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest2d - operator_name: upsample_nearest2d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact2d - operator_name: _upsample_nearest_exact2d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest2d_backward - operator_name: upsample_nearest2d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact2d_backward - operator_name: _upsample_nearest_exact2d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest3d - operator_name: upsample_nearest3d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact3d - operator_name: _upsample_nearest_exact3d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest3d_backward - operator_name: upsample_nearest3d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact3d_backward - operator_name: _upsample_nearest_exact3d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: upsample_linear1d_out operator_name: upsample_linear1d overload_name: out @@ -128360,7 +130014,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -128499,7 +130153,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int[2] dilation=1) -> Tensor + schema_string: aten::slow_conv_transpose2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, int[2] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -128624,7 +130278,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -128763,7 +130417,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int[3] dilation=1) -> Tensor + schema_string: aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129541,7 +131195,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_conv_depthwise2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, int[2] dilation, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_conv_depthwise2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, SymInt[2] padding, int[2] dilation, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -129658,7 +131312,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_conv_depthwise2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, int[2] dilation) -> Tensor + schema_string: aten::_conv_depthwise2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, SymInt[2] padding, int[2] dilation) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129761,7 +131415,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::conv_depthwise3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, int[3] dilation) -> Tensor + schema_string: aten::conv_depthwise3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, int[3] dilation) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129864,7 +131518,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -129975,7 +131629,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0) -> Tensor + schema_string: aten::slow_conv3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130072,7 +131726,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, *, Tensor(a!) output) -> Tensor(a!) + schema_string: aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, *, Tensor(a!) output) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -130177,7 +131831,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding) -> Tensor + schema_string: aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130268,7 +131922,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1) -> Tensor + schema_string: aten::slow_conv_dilated2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, int[2] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130379,7 +132033,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1) -> Tensor + schema_string: aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -147845,7 +149499,7 @@ overload_name: int manual_kernel_registration: false category_override: '' - schema_string: aten::select_copy.int(Tensor self, int dim, int index) -> Tensor + schema_string: aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -148018,7 +149672,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::split_copy.Tensor(Tensor self, int split_size, int dim=0) -> Tensor[] + schema_string: aten::split_copy.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -148075,7 +149729,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::split_with_sizes_copy(Tensor self, int[] split_sizes, int dim=0) -> Tensor[] + schema_string: aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -148207,6 +149861,51 @@ with_gil: false deprecated: false has_math_kernel: false +- name: squeeze_copy + operator_name: squeeze_copy + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze_copy.dims(Tensor self, int[] dim) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: t_copy operator_name: t_copy overload_name: '' @@ -148669,221 +150368,32 @@ with_gil: false deprecated: false has_math_kernel: false -- name: view_copy - operator_name: view_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy(Tensor self, SymInt[] size) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_copy - operator_name: view_copy - overload_name: dtype - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::ScalarType) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unfold_copy - operator_name: unfold_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dimension - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: size - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dimension - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: size - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: alias_copy - operator_name: alias_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::alias_copy(Tensor self) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _fw_primal_copy_out - operator_name: _fw_primal_copy - overload_name: out +- name: unbind_copy_out + operator_name: unbind_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) + schema_order_cpp_signature: void (const at::Tensor &, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -148891,26 +150401,24 @@ name: self type: const at::Tensor & - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -148918,117 +150426,67 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _make_dual_copy_out - operator_name: _make_dual_copy - overload_name: out +- name: split_copy_out + operator_name: split_copy + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::split_copy.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false - name: primal + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: int64_t is_nullable: false - name: tangent - type: const at::Tensor & + name: split_size + type: int64_t - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &) + schema_order_cpp_signature: void (const at::Tensor &, int64_t, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: primal - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: tangent + name: self type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: level + name: split_size type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_as_real_copy_out - operator_name: view_as_real_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & + name: dim + type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -149036,146 +150494,67 @@ with_gil: false deprecated: false has_math_kernel: false -- name: view_as_complex_copy_out - operator_name: view_as_complex_copy +- name: split_with_sizes_copy_out + operator_name: split_with_sizes_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _conj_copy_out - operator_name: _conj_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::IntArrayRef is_nullable: false - name: out - output: true - type: at::Tensor & + name: split_sizes + type: at::IntArrayRef - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + name: dim + type: int64_t + schema_order_cpp_signature: void (const at::Tensor &, at::IntArrayRef, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _neg_view_copy_out - operator_name: _neg_view_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::IntArrayRef is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + name: split_sizes + type: at::IntArrayRef - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & + name: dim + type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -149183,20 +150562,13 @@ with_gil: false deprecated: false has_math_kernel: false -- name: as_strided_copy_out - operator_name: as_strided_copy - overload_name: out +- name: view_copy + operator_name: view_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy(Tensor self, SymInt[] size) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -149207,18 +150579,7 @@ is_nullable: false name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: storage_offset - type: c10::optional - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149230,24 +150591,6 @@ is_nullable: false name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: storage_offset - type: c10::optional - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149255,8 +150598,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149264,31 +150607,24 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _sparse_broadcast_to_copy_out - operator_name: _sparse_broadcast_to_copy - overload_name: out +- name: view_copy + operator_name: view_copy + overload_name: dtype manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::ScalarType is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + name: dtype + type: at::ScalarType + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::ScalarType) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149296,17 +150632,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::ScalarType is_nullable: false - name: out - output: true - type: at::Tensor & + name: dtype + type: at::ScalarType method_of: - Type - namespace @@ -149314,8 +150643,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149323,44 +150652,34 @@ with_gil: false deprecated: false has_math_kernel: false -- name: diagonal_copy_out - operator_name: diagonal_copy - overload_name: out +- name: unfold_copy + operator_name: unfold_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: offset + name: dimension type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim1 + name: size type: int64_t - annotation: null - default: 1 dynamic_type: int64_t is_nullable: false - name: dim2 + name: step type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149368,30 +150687,20 @@ name: self type: const at::Tensor & - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: offset + name: dimension type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim1 + name: size type: int64_t - annotation: null - default: 1 dynamic_type: int64_t is_nullable: false - name: dim2 + name: step type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149399,8 +150708,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149408,63 +150717,25 @@ with_gil: false deprecated: false has_math_kernel: false -- name: expand_copy_out - operator_name: expand_copy - overload_name: out +- name: alias_copy + operator_name: alias_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::alias_copy(Tensor self) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: implicit - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: implicit - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149472,8 +150743,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149481,31 +150752,30 @@ with_gil: false deprecated: false has_math_kernel: false -- name: permute_copy_out - operator_name: permute_copy - overload_name: out +- name: to_padded_tensor + operator_name: to_padded_tensor + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: double is_nullable: false - name: dims - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + name: padding + type: double + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: output_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149513,26 +150783,25 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dims - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false - name: out - output: true - type: at::Tensor & + name: padding + type: double + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: output_size + type: at::OptionalIntArrayRef method_of: - Type - - namespace + - Tensor mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149540,36 +150809,24 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _reshape_alias_copy_out - operator_name: _reshape_alias_copy - overload_name: out +- name: _nested_tensor_softmax_with_shape + operator_name: _nested_tensor_softmax_with_shape + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: stride - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + name: query + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149577,22 +150834,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: query + type: const at::Tensor & method_of: - Type - namespace @@ -149600,8 +150845,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149609,449 +150854,219 @@ with_gil: false deprecated: false has_math_kernel: false -- name: select_copy_out - operator_name: select_copy - overload_name: int_out +- name: _transformer_encoder_layer_fwd + operator_name: _transformer_encoder_layer_fwd + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_copy.int_out(Tensor self, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: src type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: dim + name: embed_dim type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: index + name: num_heads type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: index - type: int64_t - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: detach_copy_out - operator_name: detach_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::detach_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: qkv_bias + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: proj_weight + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + - annotation: null + dynamic_type: bool + is_nullable: false + name: use_gelu + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: norm_first + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_weight_1 type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: slice_copy_out - operator_name: slice_copy - overload_name: Tensor_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: norm_bias_1 + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: norm_weight_2 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_bias_2 type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: start - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: end - type: c10::optional + name: ffn_weight_1 + type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, int64_t, at::Tensor &) - schema_order_arguments: + name: ffn_bias_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_weight_2 type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t + name: ffn_bias_2 + type: const at::Tensor & - annotation: null - default: c10::nullopt - dynamic_type: int64_t + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: start - type: c10::optional + name: mask + type: const c10::optional & - annotation: null default: c10::nullopt dynamic_type: int64_t is_nullable: true - name: end + name: mask_type type: c10::optional - - annotation: null - default: 1 - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: split_copy_out - operator_name: split_copy - overload_name: Tensor_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::split_copy.Tensor_out(Tensor self, int split_size, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool, double, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: src type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: split_size + name: embed_dim type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim + name: num_heads type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, int64_t, int64_t, at::TensorList) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: split_size - type: int64_t - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: split_with_sizes_copy_out - operator_name: split_with_sizes_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::split_with_sizes_copy.out(Tensor self, int[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_bias type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: split_sizes - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, at::IntArrayRef, int64_t, at::TensorList) - schema_order_arguments: + name: proj_weight + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: bool is_nullable: false - name: split_sizes - type: at::IntArrayRef + name: use_gelu + type: bool - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: bool is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList + name: norm_first + type: bool + - annotation: null + dynamic_type: double is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: squeeze_copy_out - operator_name: squeeze_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: eps + type: double + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: norm_weight_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_bias_1 type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_weight_2 type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: squeeze_copy_out - operator_name: squeeze_copy - overload_name: dim_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: norm_bias_2 + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: ffn_weight_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_bias_1 type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) - schema_order_arguments: + name: ffn_weight_2 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_bias_2 type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional method_of: - Type - namespace @@ -150059,8 +151074,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -150068,412 +151083,153 @@ with_gil: false deprecated: false has_math_kernel: false -- name: t_copy_out - operator_name: t_copy - overload_name: out +- name: _native_multi_head_attention + operator_name: _native_multi_head_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: transpose_copy_out - operator_name: transpose_copy - overload_name: int_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: dim0 + name: embed_dim type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: dim1 + name: num_head type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim0 - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim1 - type: int64_t - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unsqueeze_copy_out - operator_name: unsqueeze_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & + name: qkv_bias + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_weight type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _indices_copy_out - operator_name: _indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: need_weights + type: bool - annotation: null - dynamic_type: at::Tensor + default: true + dynamic_type: bool is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + name: average_attn_weights + type: bool + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, bool, bool, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _values_copy_out - operator_name: _values_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: indices_copy_out - operator_name: indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor + - annotation: null + dynamic_type: int64_t is_nullable: false - name: out - output: true - type: at::Tensor & + name: embed_dim + type: int64_t - annotation: null - dynamic_type: at::Tensor + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + name: num_head + type: int64_t - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: values_copy_out - operator_name: values_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_weight type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: crow_indices_copy_out - operator_name: crow_indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: need_weights + type: bool + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: average_attn_weights + type: bool + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional method_of: - Type - namespace @@ -150481,8 +151237,11 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -150490,409 +151249,287 @@ with_gil: false deprecated: false has_math_kernel: false -- name: col_indices_copy_out - operator_name: col_indices_copy - overload_name: out +- name: scaled_dot_product_attention + operator_name: scaled_dot_product_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unbind_copy_out - operator_name: unbind_copy - overload_name: int_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList + name: value + type: const at::Tensor & - annotation: null + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double is_nullable: false - name: self - type: const at::Tensor & + name: dropout_p + type: double - annotation: null - default: 0 - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, int64_t, at::TensorList) + name: is_causal + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_copy_out - operator_name: view_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) - schema_order_arguments: - - annotation: null + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & + is_nullable: true + name: attn_mask + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: 0.0 + dynamic_type: double is_nullable: false - name: size - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: is_causal + type: bool method_of: - Type - namespace mode: native - python_module: '' + python_module: nn returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: view_copy_out - operator_name: view_copy - overload_name: dtype_out + has_math_kernel: true +- name: _scaled_dot_product_attention + operator_name: _scaled_dot_product_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unfold_copy_out - operator_name: unfold_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: value + type: const at::Tensor & - annotation: null + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & + is_nullable: true + name: attn_mask + type: const c10::optional & - annotation: null - dynamic_type: int64_t + default: 0.0 + dynamic_type: double is_nullable: false - name: dimension - type: int64_t + name: dropout_p + type: double - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: size - type: int64_t + name: need_attn_weights + type: bool - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) + name: is_causal + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dimension - type: int64_t + name: value + type: const at::Tensor & - annotation: null - dynamic_type: int64_t + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double is_nullable: false - name: size - type: int64_t + name: dropout_p + type: double - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: step - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: need_attn_weights + type: bool + - annotation: null + default: false + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: is_causal + type: bool method_of: - Type - namespace mode: native - python_module: '' + python_module: nn returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: alias_copy_out - operator_name: alias_copy - overload_name: out + has_math_kernel: true +- name: _fused_sdp_choice + operator_name: _fused_sdp_choice + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fused_sdp_choice(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> int arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: to_padded_tensor - operator_name: to_padded_tensor - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor - arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: padding + name: dropout_p type: double - annotation: null - default: c10::nullopt - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef) + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + schema_order_cpp_signature: int64_t (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key type: const at::Tensor & - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value + type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: padding + name: dropout_p type: double - annotation: null - default: c10::nullopt - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool method_of: - Type - - Tensor + - namespace mode: native python_module: '' returns: - - dynamic_type: at::Tensor + - dynamic_type: int64_t name: result - type: at::Tensor + type: int64_t inplace: false is_factory_method: false abstract: true @@ -150900,35 +151537,93 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_softmax_with_shape - operator_name: _nested_tensor_softmax_with_shape +- name: _scaled_dot_product_attention_math + operator_name: _scaled_dot_product_attention_math overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor + schema_string: aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: query + name: key type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: dropout_mask + type: const c10::optional & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, const c10::optional &) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: query type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value + type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: dropout_mask + type: const c10::optional & method_of: - Type - namespace @@ -150936,72 +151631,134 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _nested_tensor_layer_norm - operator_name: _nested_tensor_layer_norm + has_math_kernel: true +- name: _scaled_dot_product_flash_attention + operator_name: _scaled_dot_product_flash_attention overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_layer_norm(Tensor self, Tensor? weight, Tensor? bias, float eps) -> Tensor + schema_string: aten::_scaled_dot_product_flash_attention(Tensor query, Tensor key, Tensor value, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False) -> (Tensor ouput, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, int philox_seed, int philox_offset, Tensor debug_attn_mask) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & + is_nullable: false + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const c10::optional &, const c10::optional &, double) + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & + is_nullable: false + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool method_of: - Type - - Tensor + - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: result + field_name: ouput + name: ouput + type: at::Tensor + - dynamic_type: at::Tensor + field_name: logsumexp + name: logsumexp + type: at::Tensor + - dynamic_type: at::Tensor + field_name: cum_seq_q + name: cum_seq_q + type: at::Tensor + - dynamic_type: at::Tensor + field_name: cum_seq_k + name: cum_seq_k + type: at::Tensor + - dynamic_type: int64_t + field_name: max_q + name: max_q + type: int64_t + - dynamic_type: int64_t + field_name: max_k + name: max_k + type: int64_t + - dynamic_type: int64_t + field_name: philox_seed + name: philox_seed + type: int64_t + - dynamic_type: int64_t + field_name: philox_offset + name: philox_offset + type: int64_t + - dynamic_type: at::Tensor + field_name: debug_attn_mask + name: debug_attn_mask type: at::Tensor inplace: false is_factory_method: false @@ -151010,219 +151767,353 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _transformer_encoder_layer_fwd - operator_name: _transformer_encoder_layer_fwd +- name: _scaled_dot_product_flash_attention_backward + operator_name: _scaled_dot_product_flash_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor + schema_string: aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: src + name: grad_out type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: embed_dim - type: int64_t + name: query + type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: num_heads - type: int64_t + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: logsumexp type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: cum_seq_q type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - name: use_gelu - type: bool + name: cum_seq_k + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: norm_first - type: bool + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, int64_t, int64_t) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_1 + name: grad_out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_1 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_2 + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_2 + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_1 + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_1 + name: logsumexp type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_2 + name: cum_seq_q type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_2 + name: cum_seq_k type: const at::Tensor & - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t - annotation: null - default: c10::nullopt dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool, double, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional) - schema_order_arguments: + is_nullable: false + name: max_k + type: int64_t - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false - name: src - type: const at::Tensor & + name: dropout_p + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool - annotation: null dynamic_type: int64_t is_nullable: false - name: embed_dim + name: philox_seed type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: num_heads + name: philox_offset type: int64_t + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: grad_query + name: grad_query + type: at::Tensor + - dynamic_type: at::Tensor + field_name: grad_key + name: grad_key + type: at::Tensor + - dynamic_type: at::Tensor + field_name: grad_value + name: grad_value + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _scaled_dot_product_efficient_attention + operator_name: _scaled_dot_product_efficient_attention + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_scaled_dot_product_efficient_attention(Tensor query, Tensor key, Tensor value, bool compute_log_sumexp, bool is_causal=False) -> (Tensor, Tensor) + arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: value type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: compute_log_sumexp + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value type: const at::Tensor & - annotation: null dynamic_type: bool is_nullable: false - name: use_gelu + name: compute_log_sumexp type: bool - annotation: null + default: false dynamic_type: bool is_nullable: false - name: norm_first + name: is_causal type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _scaled_dot_product_efficient_attention_backward + operator_name: _scaled_dot_product_efficient_attention_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_scaled_dot_product_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor) + arguments: - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: eps - type: double + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_1 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_1 + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_2 + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_2 + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_1 + name: logsumexp type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: chunk_grad_outputs + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_1 + name: grad_out_ type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_2 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_2 + name: key type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional + dynamic_type: at::Tensor + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: chunk_grad_outputs + type: bool method_of: - Type - namespace @@ -151230,7 +152121,13 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 type: at::Tensor inplace: false is_factory_method: false @@ -151239,12 +152136,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _native_multi_head_attention - operator_name: _native_multi_head_attention +- name: _chunk_grad_outputs_efficient_attention + operator_name: _chunk_grad_outputs_efficient_attention overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) + schema_string: aten::_chunk_grad_outputs_efficient_attention(Tensor query, Tensor key, Tensor value, bool is_causal=False) -> bool arguments: - annotation: null dynamic_type: at::Tensor @@ -151262,61 +152159,57 @@ name: value type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: embed_dim - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: num_head - type: int64_t - - annotation: null - dynamic_type: at::Tensor + default: false + dynamic_type: bool is_nullable: false - name: qkv_weight - type: const at::Tensor & + name: is_causal + type: bool + schema_order_cpp_signature: bool (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: value type: const at::Tensor & - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & - - annotation: null - default: true + default: false dynamic_type: bool is_nullable: false - name: need_weights + name: is_causal type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: average_attn_weights + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: bool + name: result type: bool - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, bool, bool, c10::optional) - schema_order_arguments: + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _flash_attention_forward + operator_name: _flash_attention_forward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, bool return_debug_mask) -> (Tensor output, Tensor softmax_logsumexp, int philox_seed, int philox_offset, Tensor debug_attn_mask) + arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151332,60 +152225,93 @@ is_nullable: false name: value type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: embed_dim + name: max_q type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: num_head + name: max_k type: int64_t + - annotation: null + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: cum_seq_q type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t + - annotation: null + dynamic_type: double + is_nullable: false + name: dropout_p + type: double - annotation: null - default: true dynamic_type: bool is_nullable: false - name: need_weights + name: is_causal type: bool - annotation: null - default: true dynamic_type: bool is_nullable: false - name: average_attn_weights + name: return_debug_mask type: bool - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional method_of: - Type - namespace @@ -151393,10 +152319,24 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result0 + field_name: output + name: output type: at::Tensor - dynamic_type: at::Tensor - name: result1 + field_name: softmax_logsumexp + name: softmax_logsumexp + type: at::Tensor + - dynamic_type: int64_t + field_name: philox_seed + name: philox_seed + type: int64_t + - dynamic_type: int64_t + field_name: philox_offset + name: philox_offset + type: int64_t + - dynamic_type: at::Tensor + field_name: debug_attn_mask + name: debug_attn_mask type: at::Tensor inplace: false is_factory_method: false @@ -151405,13 +152345,18 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _scaled_dot_product_attention - operator_name: _scaled_dot_product_attention +- name: _flash_attention_backward + operator_name: _flash_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor, Tensor, Tensor) arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151428,31 +152373,62 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null - default: 0.0 dynamic_type: double is_nullable: false name: dropout_p type: double - annotation: null - default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null - default: false - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: is_causal - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, int64_t, int64_t) schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151469,34 +152445,60 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null - default: 0.0 dynamic_type: double is_nullable: false name: dropout_p type: double - annotation: null - default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null - default: false - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: is_causal - type: bool + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t method_of: - Type - namespace mode: native - python_module: nn + python_module: '' returns: - dynamic_type: at::Tensor name: result0 @@ -151504,19 +152506,22 @@ - dynamic_type: at::Tensor name: result1 type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true -- name: _scaled_dot_product_attention_forward - operator_name: _scaled_dot_product_attention_forward + has_math_kernel: false +- name: _efficient_attention_forward + operator_name: _efficient_attention_forward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, int? max_seqlen_q, bool compute_log_sumexp=False, bool causal=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -151534,30 +152539,33 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor is_nullable: true - name: attn_mask + name: cu_seqlens_q type: const c10::optional & - annotation: null - default: 0.0 - dynamic_type: double - is_nullable: false - name: dropout_p - type: double + dynamic_type: at::Tensor + is_nullable: true + name: cu_seqlens_k + type: const c10::optional & + - annotation: null + dynamic_type: int64_t + is_nullable: true + name: max_seqlen_q + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: compute_log_sumexp type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: causal type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, c10::optional, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -151575,28 +152583,31 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor is_nullable: true - name: attn_mask + name: cu_seqlens_q type: const c10::optional & - annotation: null - default: 0.0 - dynamic_type: double - is_nullable: false - name: dropout_p - type: double + dynamic_type: at::Tensor + is_nullable: true + name: cu_seqlens_k + type: const c10::optional & + - annotation: null + dynamic_type: int64_t + is_nullable: true + name: max_seqlen_q + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: compute_log_sumexp type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: causal type: bool method_of: - Type @@ -151617,13 +152628,18 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _scaled_dot_product_attention_math - operator_name: _scaled_dot_product_attention_math +- name: _efficient_attention_backward + operator_name: _efficient_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor) arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151640,31 +152656,34 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & - annotation: null - default: 0.0 - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: dropout_p - type: double + name: logsumexp + type: const at::Tensor & - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: chunk_grad_outputs type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151681,28 +152700,26 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & - annotation: null - default: 0.0 - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: dropout_p - type: double + name: logsumexp + type: const at::Tensor & - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: chunk_grad_outputs type: bool method_of: - Type @@ -151716,13 +152733,16 @@ - dynamic_type: at::Tensor name: result1 type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: _triton_scaled_dot_attention operator_name: _triton_scaled_dot_attention overload_name: '' @@ -152001,121 +153021,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _flash_scaled_dot_product_attention - operator_name: _flash_scaled_dot_product_attention - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_flash_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: query - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: key - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: value - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_q - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_k - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_q - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_k - type: int64_t - - annotation: null - dynamic_type: double - is_nullable: false - name: dropout_p - type: double - - annotation: null - dynamic_type: bool - is_nullable: false - name: is_causal - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: query - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: key - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: value - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_q - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_k - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_q - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_k - type: int64_t - - annotation: null - dynamic_type: double - is_nullable: false - name: dropout_p - type: double - - annotation: null - dynamic_type: bool - is_nullable: false - name: is_causal - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false - name: _transformer_decoder_only_layer_fwd operator_name: _transformer_decoder_only_layer_fwd overload_name: '' @@ -157482,6 +158387,200 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _fused_adamw_ + operator_name: _fused_adamw_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: _new_zeros_with_same_feature_meta_out operator_name: _new_zeros_with_same_feature_meta overload_name: out @@ -159780,7 +160879,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::constant_pad_nd.out(Tensor self, int[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -159851,7 +160950,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -159980,7 +161079,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + schema_string: aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) arguments: - allocate: true annotation: a! @@ -160465,7 +161564,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -162568,6 +163667,126 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _ctc_loss_out + operator_name: _ctc_loss + overload_name: Tensor_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: log_probs + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: targets + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input_lengths + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: target_lengths + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: blank + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: zero_infinity + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: log_probs + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: targets + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input_lengths + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: target_lengths + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: blank + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: zero_infinity + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _ctc_loss_backward_out operator_name: _ctc_loss_backward overload_name: out @@ -163008,7 +164227,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::embedding.out(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -163103,7 +164322,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -163720,7 +164939,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -168009,127 +169228,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _mps_max_pool2d_out - operator_name: _mps_max_pool2d +- name: max_pool2d_backward_out + operator_name: max_pool2d_backward overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_mps_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: mps_max_pool2d_backward_out - operator_name: mps_max_pool2d_backward - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mps_max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -169214,107 +170318,825 @@ name: out2 output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - annotation: null - dynamic_type: ::std::array - is_nullable: false - name: output_mask - type: ::std::array - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_convolution_out + operator_name: mkldnn_convolution + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_out + operator_name: mkldnn_rnn_layer + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out3 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_backward_out + operator_name: mkldnn_rnn_layer_backward + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: out4 + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & + - allocate: true + annotation: g! + dynamic_type: at::Tensor + is_nullable: false + name: out6 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! dynamic_type: at::Tensor is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - annotation: null - dynamic_type: ::std::array - is_nullable: false - name: output_mask - type: ::std::array + name: out3 + output: true + type: at::Tensor & - allocate: true - annotation: a! + annotation: e! dynamic_type: at::Tensor is_nullable: false - name: out0 + name: out4 output: true type: at::Tensor & - allocate: true - annotation: b! + annotation: f! dynamic_type: at::Tensor is_nullable: false - name: out1 + name: out5 output: true type: at::Tensor & - allocate: true - annotation: c! + annotation: g! dynamic_type: at::Tensor is_nullable: false - name: out2 + name: out6 output: true type: at::Tensor & method_of: @@ -169332,114 +171154,17 @@ - dynamic_type: at::Tensor name: out2 type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_convolution_out - operator_name: mkldnn_convolution - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true + - dynamic_type: at::Tensor + name: out3 type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true + - dynamic_type: at::Tensor + name: out4 type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - dynamic_type: at::Tensor - name: out + name: out5 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out6 type: at::Tensor & inplace: false is_factory_method: false @@ -169759,7 +171484,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -169888,7 +171613,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170027,7 +171752,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170745,12 +172470,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _sparse_mask_helper_out - operator_name: _sparse_mask_helper - overload_name: out +- name: mul_out + operator_name: mul + overload_name: Scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_mask_helper.out(Tensor t, Tensor mask_indices, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170762,25 +172487,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: t + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: const at::Scalar & is_nullable: false - name: mask_indices - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) + name: other + type: const at::Scalar & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: t + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: const at::Scalar & is_nullable: false - name: mask_indices - type: const at::Tensor & + name: other + type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -170804,49 +172529,95 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mul_out - operator_name: mul - overload_name: Scalar_out +- name: _native_batch_norm_legit_functional + operator_name: _native_batch_norm_legit_functional + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_native_batch_norm_legit_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out) arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: running_mean type: const at::Tensor & - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Scalar & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &) + name: running_var + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, bool, double, double) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: input type: const at::Tensor & - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Scalar & - - allocate: true - annotation: a! + name: running_mean + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: running_var + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double method_of: - Type - namespace @@ -170854,8 +172625,22 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + field_name: running_mean_out + name: running_mean_out + type: at::Tensor + - dynamic_type: at::Tensor + field_name: running_var_out + name: running_var_out + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -171774,7 +173559,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[2] padding, int[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, int[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -172647,7 +174432,7 @@ overload_name: names_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -172708,7 +174493,7 @@ overload_name: generator_with_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_with_names_out(int[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173000,7 +174785,7 @@ overload_name: names_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173061,7 +174846,7 @@ overload_name: generator_with_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_with_names_out(int[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173373,179 +175158,37 @@ with_gil: false deprecated: false has_math_kernel: false -- name: relu_out - operator_name: relu - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: prelu_out - operator_name: prelu - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::prelu.out(Tensor self, Tensor weight, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: prelu_backward_out - operator_name: prelu_backward +- name: relu_out + operator_name: relu overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::prelu_backward.out(Tensor grad_output, Tensor self, Tensor weight, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 + name: out output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 + name: out output: true type: at::Tensor & method_of: @@ -173555,10 +175198,7 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 + name: out type: at::Tensor & inplace: false is_factory_method: false @@ -173572,7 +175212,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173918,7 +175558,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::select_scatter.out(Tensor self, Tensor src, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -174183,7 +175823,7 @@ overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split.Tensor_out(Tensor self, int split_size, int dim=0, *, Tensor(a!)[] out) -> () + schema_string: aten::unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -174251,7 +175891,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split_with_sizes.out(Tensor self, int[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () + schema_string: aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -174382,7 +176022,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::std_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -174404,12 +176044,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -174430,12 +176072,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -176060,7 +177704,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::var_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -176082,12 +177726,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -176108,12 +177754,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -178691,7 +180339,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, int[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179528,7 +181176,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179542,13 +181190,57 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::OptionalIntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179577,7 +181269,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179591,13 +181283,25 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179626,7 +181330,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_csc.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179640,13 +181344,25 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179675,7 +181391,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179695,7 +181411,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179708,6 +181430,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179736,7 +181464,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179756,7 +181484,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179769,6 +181503,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179858,7 +181598,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_reorder_conv2d_weight.out(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::mkldnn_reorder_conv2d_weight.out(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, int[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179899,7 +181639,13 @@ is_nullable: false name: groups type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::OptionalIntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179933,6 +181679,12 @@ is_nullable: false name: groups type: int64_t + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -181843,7 +183595,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_lstm_mps.out(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) + schema_string: aten::_lstm_mps.out(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!)) arguments: - allocate: true annotation: a! @@ -181880,6 +183632,13 @@ name: out4 output: true type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -181925,7 +183684,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -182007,6 +183766,13 @@ name: out4 output: true type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & method_of: - Type - namespace @@ -182028,6 +183794,9 @@ - dynamic_type: at::Tensor name: out4 type: at::Tensor & + - dynamic_type: at::Tensor + name: out5 + type: at::Tensor & inplace: false is_factory_method: false abstract: true @@ -182040,7 +183809,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::lstm_mps_backward.out(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> () + schema_string: aten::lstm_mps_backward.out(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> () arguments: - allocate: true annotation: a! @@ -182093,6 +183862,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -182133,7 +183907,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: void (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList) + schema_order_cpp_signature: void (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -182165,6 +183939,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -185866,92 +187645,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _symeig_helper_out - operator_name: _symeig_helper - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_symeig_helper.out(Tensor self, bool eigenvectors, bool upper, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: _cholesky_solve_helper_out operator_name: _cholesky_solve_helper overload_name: out @@ -186531,7 +188224,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::unfold_backward.out(Tensor grad_in, int[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -187072,12 +188765,544 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub - overload_name: Scalar_out +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_div_out + operator_name: _foreach_div + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_maximum_out + operator_name: _foreach_maximum + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_minimum_out + operator_name: _foreach_minimum + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add_out + operator_name: _foreach_add + overload_name: List_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: List_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187092,11 +189317,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187104,10 +189329,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187128,12 +189353,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul - overload_name: Scalar_out +- name: _foreach_div_out + operator_name: _foreach_div + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187148,11 +189373,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187160,10 +189385,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187184,12 +189409,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_out - operator_name: _foreach_div - overload_name: Scalar_out +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187204,11 +189429,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187216,10 +189441,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187240,12 +189465,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_out - operator_name: _foreach_add +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187264,14 +189489,7 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187283,13 +189501,6 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187310,12 +189521,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub +- name: _foreach_maximum_out + operator_name: _foreach_maximum overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187334,14 +189545,7 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187353,13 +189557,6 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187380,12 +189577,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul +- name: _foreach_minimum_out + operator_name: _foreach_minimum overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187436,12 +189633,124 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _foreach_add_out + operator_name: _foreach_add + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _foreach_div_out operator_name: _foreach_div - overload_name: List_out + overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187455,23 +189764,79 @@ is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) - schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187492,12 +189857,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_out - operator_name: _foreach_add +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187548,12 +189913,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187604,12 +189969,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_out - operator_name: _foreach_div +- name: _foreach_maximum_out + operator_name: _foreach_maximum overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187660,12 +190025,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul +- name: _foreach_minimum_out + operator_name: _foreach_minimum overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189318,6 +191683,82 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _foreach_addcdiv_out + operator_name: _foreach_addcdiv + overload_name: Tensor_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _foreach_addcmul_out operator_name: _foreach_addcmul overload_name: ScalarList_out @@ -189394,12 +191835,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum_out - operator_name: _foreach_maximum - overload_name: List_out +- name: _foreach_addcmul_out + operator_name: _foreach_addcmul + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_addcmul.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189416,9 +191857,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189428,8 +191879,18 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -189450,12 +191911,70 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum_out - operator_name: _foreach_minimum +- name: _foreach_norm_out + operator_name: _foreach_norm + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_out + operator_name: _foreach_lerp overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189472,9 +191991,14 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensors1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189484,7 +192008,12 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights type: at::TensorList - allocate: true annotation: a! @@ -189506,12 +192035,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_norm_out - operator_name: _foreach_norm +- name: _foreach_lerp_out + operator_name: _foreach_lerp overload_name: Scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189526,12 +192055,16 @@ name: self type: at::TensorList - annotation: null - default: 2 + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null dynamic_type: const at::Scalar & is_nullable: false - name: ord + name: weight type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189539,10 +192072,14 @@ name: self type: at::TensorList - annotation: null - default: 2 + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null dynamic_type: const at::Scalar & is_nullable: false - name: ord + name: weight type: const at::Scalar & - allocate: true annotation: a! @@ -189651,55 +192188,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _torch_cuda_cu_linker_symbol_op_out - operator_name: _torch_cuda_cu_linker_symbol_op - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_torch_cuda_cu_linker_symbol_op.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: searchsorted_out operator_name: searchsorted overload_name: Scalar_out @@ -190345,7 +192833,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_adaptive_avg_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190460,12 +192948,161 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_linear1d_out - operator_name: upsample_linear1d - overload_name: vec_out +- name: _slow_conv2d_backward_out + operator_name: _slow_conv2d_backward + overload_name: output_mask_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_linear1d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: conv_depthwise3d_out + operator_name: conv_depthwise3d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::conv_depthwise3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, int[3] dilation, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190477,45 +193114,551 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: bias + type: const c10::optional & - annotation: null - dynamic_type: bool + dynamic_type: at::IntArrayRef is_nullable: false - name: align_corners - type: bool + name: stride + size: 3 + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::Tensor is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: slow_conv_dilated2d_out + operator_name: slow_conv_dilated2d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: slow_conv_dilated3d_out + operator_name: slow_conv_dilated3d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: isinf_out + operator_name: isinf + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: linalg_matrix_exp_out + operator_name: linalg_matrix_exp + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_optional_intlist_out + operator_name: _test_optional_intlist + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: true + name: addends + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: true + name: addends + type: at::OptionalIntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_optional_filled_intlist_out + operator_name: _test_optional_filled_intlist + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_optional_filled_intlist.out(Tensor values, int[2]? addends, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true - name: output_size + name: addends + size: 2 type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_arguments: - annotation: null - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - name: align_corners - type: bool + name: values + type: const at::Tensor & - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::IntArrayRef is_nullable: true - name: scale_factors - type: c10::optional> + name: addends + size: 2 + type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190539,12 +193682,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_linear1d_backward_out - operator_name: upsample_linear1d_backward - overload_name: vec_out +- name: _test_optional_floatlist_out + operator_name: _test_optional_floatlist + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_linear1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190556,54 +193699,24 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: values type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true - name: scale_factors + name: addends type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional>, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: values type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true - name: scale_factors + name: addends type: c10::optional> - allocate: true annotation: a! @@ -190628,12 +193741,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bilinear2d_out - operator_name: upsample_bilinear2d - overload_name: vec_out +- name: _test_warn_in_autograd_out + operator_name: _test_warn_in_autograd + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190645,45 +193758,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190707,12 +193790,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bilinear2d_backward_out - operator_name: upsample_bilinear2d_backward - overload_name: vec_out +- name: _test_autograd_multiple_dispatch_out + operator_name: _test_autograd_multiple_dispatch + overload_name: fullcoverage_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190724,55 +193807,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190796,12 +193839,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bilinear2d_aa_out - operator_name: _upsample_bilinear2d_aa - overload_name: vec_out +- name: _test_autograd_multiple_dispatch_view_copy_out + operator_name: _test_autograd_multiple_dispatch_view_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190813,45 +193856,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190875,12 +193888,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bilinear2d_aa_backward_out - operator_name: _upsample_bilinear2d_aa_backward - overload_name: vec_out +- name: segment_reduce_out + operator_name: segment_reduce + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190892,55 +193905,109 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: data type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: indices + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + kwarg_only: true + name: axis + type: int64_t - annotation: null + default: false dynamic_type: bool is_nullable: false - name: align_corners + kwarg_only: true + name: unsafe type: bool - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + kwarg_only: true + name: initial + type: const c10::optional & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, const c10::optional &, int64_t, bool, const c10::optional &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: data type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: indices + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + kwarg_only: true + name: axis + type: int64_t - annotation: null + default: false dynamic_type: bool is_nullable: false - name: align_corners + kwarg_only: true + name: unsafe type: bool - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> + kwarg_only: true + name: initial + type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190964,12 +194031,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_trilinear3d_out - operator_name: upsample_trilinear3d - overload_name: vec_out +- name: _segment_reduce_backward_out + operator_name: _segment_reduce_backward + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190981,45 +194048,101 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: grad type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: data + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: bool + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool + kwarg_only: true + name: axis + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + kwarg_only: true + name: initial + type: const c10::optional & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, int64_t, const c10::optional &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: grad type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: data + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: bool + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool + kwarg_only: true + name: axis + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> + kwarg_only: true + name: initial + type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191043,12 +194166,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_trilinear3d_backward_out - operator_name: upsample_trilinear3d_backward - overload_name: vec_out +- name: _nested_tensor_from_tensor_list_out + operator_name: _nested_tensor_from_tensor_list + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191058,57 +194181,65 @@ output: true type: at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: grad_output - type: const at::Tensor & + name: list + type: at::TensorList - annotation: null - dynamic_type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::ScalarType is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: dtype + type: c10::optional - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + name: layout + type: c10::optional - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool + default: c10::nullopt + dynamic_type: at::Device + is_nullable: true + name: device + type: c10::optional - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: bool is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + name: pin_memory + type: c10::optional + schema_order_cpp_signature: at::Tensor & (at::TensorList, c10::optional, c10::optional, c10::optional, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: grad_output - type: const at::Tensor & + name: list + type: at::TensorList - annotation: null - dynamic_type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::ScalarType is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: dtype + type: c10::optional - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + name: layout + type: c10::optional - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool + default: c10::nullopt + dynamic_type: at::Device + is_nullable: true + name: device + type: c10::optional - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: bool is_nullable: true - name: scale_factors - type: c10::optional> + name: pin_memory + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191132,12 +194263,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bicubic2d_out - operator_name: upsample_bicubic2d - overload_name: vec_out +- name: _fw_primal_copy_out + operator_name: _fw_primal_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191149,45 +194280,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + name: level + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + name: level + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191211,12 +194322,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bicubic2d_backward_out - operator_name: upsample_bicubic2d_backward - overload_name: vec_out +- name: _make_dual_copy_out + operator_name: _make_dual_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191228,55 +194339,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: primal type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: input_size - type: at::IntArrayRef + name: tangent + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + name: level + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: primal type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: input_size - type: at::IntArrayRef + name: tangent + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + name: level + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191300,12 +194391,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bicubic2d_aa_out - operator_name: _upsample_bicubic2d_aa - overload_name: vec_out +- name: view_as_real_copy_out + operator_name: view_as_real_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191317,45 +194408,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191379,12 +194440,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bicubic2d_aa_backward_out - operator_name: _upsample_bicubic2d_aa_backward - overload_name: vec_out +- name: view_as_complex_copy_out + operator_name: view_as_complex_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191396,55 +194457,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191468,12 +194489,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest1d_out - operator_name: upsample_nearest1d - overload_name: vec_out +- name: _conj_copy_out + operator_name: _conj_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191485,35 +194506,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191537,12 +194538,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact1d_out - operator_name: _upsample_nearest_exact1d - overload_name: vec_out +- name: _neg_view_copy_out + operator_name: _neg_view_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact1d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191554,35 +194555,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191606,12 +194587,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest1d_backward_out - operator_name: upsample_nearest1d_backward - overload_name: vec_out +- name: as_strided_copy_out + operator_name: as_strided_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191623,45 +194604,47 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + name: storage_offset + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> + name: storage_offset + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191685,12 +194668,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact1d_backward_out - operator_name: _upsample_nearest_exact1d_backward - overload_name: vec_out +- name: _sparse_broadcast_to_copy_out + operator_name: _sparse_broadcast_to_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191702,45 +194685,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191764,12 +194727,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest2d_out - operator_name: upsample_nearest2d - overload_name: vec_out +- name: diagonal_copy_out + operator_name: diagonal_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191781,35 +194744,51 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: 0 + dynamic_type: int64_t + is_nullable: false + name: offset + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + default: 0 + dynamic_type: int64_t + is_nullable: false + name: dim1 + type: int64_t + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: dim2 + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: 0 + dynamic_type: int64_t + is_nullable: false + name: offset + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + default: 0 + dynamic_type: int64_t + is_nullable: false + name: dim1 + type: int64_t + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: dim2 + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191833,12 +194812,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact2d_out - operator_name: _upsample_nearest_exact2d - overload_name: vec_out +- name: expand_copy_out + operator_name: expand_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191850,35 +194829,39 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: implicit + type: bool + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: implicit + type: bool - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191902,12 +194885,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest2d_backward_out - operator_name: upsample_nearest2d_backward - overload_name: vec_out +- name: permute_copy_out + operator_name: permute_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191919,45 +194902,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: dims type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: dims type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191981,12 +194944,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact2d_backward_out - operator_name: _upsample_nearest_exact2d_backward - overload_name: vec_out +- name: _reshape_alias_copy_out + operator_name: _reshape_alias_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191998,45 +194961,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192060,12 +195013,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest3d_out - operator_name: upsample_nearest3d - overload_name: vec_out +- name: select_copy_out + operator_name: select_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest3d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192077,35 +195030,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + dynamic_type: int64_t + is_nullable: false + name: index + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: self + type: const at::Tensor & - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: index + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192129,12 +195082,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact3d_out - operator_name: _upsample_nearest_exact3d - overload_name: vec_out +- name: detach_copy_out + operator_name: detach_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact3d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::detach_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192146,35 +195099,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192198,12 +195131,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest3d_backward_out - operator_name: upsample_nearest3d_backward - overload_name: vec_out +- name: slice_copy_out + operator_name: slice_copy + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192215,45 +195148,63 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + name: start + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: end + type: c10::optional + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> + name: start + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: end + type: c10::optional + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192277,12 +195228,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact3d_backward_out - operator_name: _upsample_nearest_exact3d_backward - overload_name: vec_out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192294,45 +195245,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192356,131 +195277,47 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _slow_conv2d_backward_out - operator_name: _slow_conv2d_backward - overload_name: output_mask_out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: dim_out manual_kernel_registration: false category_override: '' - schema_string: aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + schema_string: aten::squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - is_nullable: false - name: out2 + name: out output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: ::std::array + dynamic_type: int64_t is_nullable: false - name: output_mask - type: ::std::array - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + name: dim + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: ::std::array + dynamic_type: int64_t is_nullable: false - name: output_mask - type: ::std::array + name: dim + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - is_nullable: false - name: out2 + name: out output: true type: at::Tensor & method_of: @@ -192490,13 +195327,7 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out2 + name: out type: at::Tensor & inplace: false is_factory_method: false @@ -192505,12 +195336,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: conv_depthwise3d_out - operator_name: conv_depthwise3d - overload_name: out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: dims_out manual_kernel_registration: false category_override: '' - schema_string: aten::conv_depthwise3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, int[3] dilation, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::squeeze_copy.dims_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192524,80 +195355,22 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 + name: dim type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: dilation - size: 3 + name: dim type: at::IntArrayRef - allocate: true annotation: a! @@ -192622,12 +195395,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: slow_conv_dilated2d_out - operator_name: slow_conv_dilated2d +- name: t_copy_out + operator_name: t_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192641,89 +195414,13 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192747,12 +195444,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: slow_conv_dilated3d_out - operator_name: slow_conv_dilated3d - overload_name: out +- name: transpose_copy_out + operator_name: transpose_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192767,44 +195464,16 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef + name: dim0 + type: int64_t - annotation: null - default: 1 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + name: dim1 + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -192812,43 +195481,15 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef + name: dim0 + type: int64_t - annotation: null - default: 1 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef + name: dim1 + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192872,12 +195513,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: isinf_out - operator_name: isinf +- name: unsqueeze_copy_out + operator_name: unsqueeze_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192891,13 +195532,23 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192921,12 +195572,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: linalg_matrix_exp_out - operator_name: linalg_matrix_exp +- name: _indices_copy_out + operator_name: _indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192970,12 +195621,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_intlist_out - operator_name: _test_optional_intlist +- name: _values_copy_out + operator_name: _values_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192987,25 +195638,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193029,12 +195670,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_filled_intlist_out - operator_name: _test_optional_filled_intlist +- name: indices_copy_out + operator_name: indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_filled_intlist.out(Tensor values, int[2]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193046,27 +195687,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - size: 2 - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - size: 2 - type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193090,12 +195719,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_floatlist_out - operator_name: _test_optional_floatlist +- name: values_copy_out + operator_name: values_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193107,25 +195736,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: addends - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: addends - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193149,12 +195768,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_warn_in_autograd_out - operator_name: _test_warn_in_autograd +- name: crow_indices_copy_out + operator_name: crow_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193198,12 +195817,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_autograd_multiple_dispatch_out - operator_name: _test_autograd_multiple_dispatch - overload_name: fullcoverage_out +- name: col_indices_copy_out + operator_name: col_indices_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193247,12 +195866,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_autograd_multiple_dispatch_view_copy_out - operator_name: _test_autograd_multiple_dispatch_view_copy +- name: ccol_indices_copy_out + operator_name: ccol_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::ccol_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193296,12 +195915,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: segment_reduce_out - operator_name: segment_reduce +- name: row_indices_copy_out + operator_name: row_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::row_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193313,109 +195932,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: data + name: self type: const at::Tensor & - - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: indices - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: unsafe - type: bool - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, const c10::optional &, int64_t, bool, const c10::optional &, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: data + name: self type: const at::Tensor & - - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: indices - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: unsafe - type: bool - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193439,12 +195964,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _segment_reduce_backward_out - operator_name: _segment_reduce_backward +- name: view_copy_out + operator_name: view_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193456,101 +195981,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: data + name: self type: const at::Tensor & - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::IntArrayRef is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, int64_t, const c10::optional &, at::Tensor &) + name: size + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: data + name: self type: const at::Tensor & - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::IntArrayRef is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & + name: size + type: at::IntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193574,12 +196023,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_from_tensor_list_out - operator_name: _nested_tensor_from_tensor_list - overload_name: out +- name: view_copy_out + operator_name: view_copy + overload_name: dtype_out manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193589,65 +196038,27 @@ output: true type: at::Tensor & - annotation: null - dynamic_type: at::TensorList + dynamic_type: at::Tensor is_nullable: false - name: list - type: at::TensorList + name: self + type: const at::Tensor & - annotation: null - default: c10::nullopt dynamic_type: at::ScalarType - is_nullable: true + is_nullable: false name: dtype - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Layout - is_nullable: true - name: layout - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Device - is_nullable: true - name: device - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: bool - is_nullable: true - name: pin_memory - type: c10::optional - schema_order_cpp_signature: at::Tensor & (at::TensorList, c10::optional, c10::optional, c10::optional, c10::optional, at::Tensor &) + type: at::ScalarType + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::TensorList + dynamic_type: at::Tensor is_nullable: false - name: list - type: at::TensorList + name: self + type: const at::Tensor & - annotation: null - default: c10::nullopt dynamic_type: at::ScalarType - is_nullable: true + is_nullable: false name: dtype - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Layout - is_nullable: true - name: layout - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Device - is_nullable: true - name: device - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: bool - is_nullable: true - name: pin_memory - type: c10::optional + type: at::ScalarType - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193671,12 +196082,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: ccol_indices_copy_out - operator_name: ccol_indices_copy +- name: unfold_copy_out + operator_name: unfold_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::ccol_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193690,13 +196101,43 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dimension + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dimension + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193720,12 +196161,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: row_indices_copy_out - operator_name: row_indices_copy +- name: alias_copy_out + operator_name: alias_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::row_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193774,7 +196215,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_padded_tensor.out(Tensor self, float padding, int[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193840,85 +196281,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_layer_norm_out - operator_name: _nested_tensor_layer_norm - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_nested_tensor_layer_norm.out(Tensor self, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: double - is_nullable: false - name: eps - type: double - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const c10::optional &, const c10::optional &, double, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: double - is_nullable: false - name: eps - type: double - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: _transformer_encoder_layer_fwd_out operator_name: _transformer_encoder_layer_fwd overload_name: out @@ -195616,3 +197978,425 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _fused_adamw_out + operator_name: _fused_adamw + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _fused_adamw + operator_name: _fused_adamw + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + field_name: self_out + name: self_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: grads_out + name: grads_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: exp_avgs_out + name: exp_avgs_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: exp_avg_sqs_out + name: exp_avg_sqs_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: max_exp_avg_sqs_out + name: max_exp_avg_sqs_out + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false diff --git a/src/lantern/include/lantern/lantern.h b/src/lantern/include/lantern/lantern.h index 7a3706a453..4224b2ee4a 100644 --- a/src/lantern/include/lantern/lantern.h +++ b/src/lantern/include/lantern/lantern.h @@ -2865,6 +2865,16 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_affine_grid_generator_tensor_intarrayref_bool(void* theta, void* size, void* align_corners) { LANTERN_CHECK_LOADED void* ret = _lantern_affine_grid_generator_tensor_intarrayref_bool(theta, size, align_corners); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_affine_grid_generator_backward_tensor_intarrayref_bool)(void* grad, void* size, void* align_corners); HOST_API void* lantern_affine_grid_generator_backward_tensor_intarrayref_bool(void* grad, void* size, void* align_corners) { LANTERN_CHECK_LOADED void* ret = _lantern_affine_grid_generator_backward_tensor_intarrayref_bool(grad, size, align_corners); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__is_all_true_tensor)(void* self); + HOST_API void* lantern__is_all_true_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__is_all_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor__is_all_true_tensor)(void* self); + HOST_API void* lantern_Tensor__is_all_true_tensor(void* self) { void* ret = _lantern_Tensor__is_all_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__is_any_true_tensor)(void* self); + HOST_API void* lantern__is_any_true_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__is_any_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor__is_any_true_tensor)(void* self); + HOST_API void* lantern_Tensor__is_any_true_tensor(void* self) { void* ret = _lantern_Tensor__is_any_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__test_check_tensor_tensor)(void* self); + HOST_API void* lantern__test_check_tensor_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__test_check_tensor_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_all_tensor_intt_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_all_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_all_tensor_intt_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_all_tensor_intt_bool)(void* self, void* dim, void* keepdim); @@ -4279,10 +4289,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); + HOST_API void* lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* output, void* input, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); @@ -4375,6 +4383,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(void* self, void* grad_output, void* weight, void* padding, void* stride, void* dilation, void* groups, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(self, grad_output, weight, padding, stride, dilation, groups, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(self, weight, bias, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool)(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train); + HOST_API void* lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor)(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace); + HOST_API void* lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon); HOST_API void* lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double)(void* input, void* grad_output, void* weight, void* running_mean, void* running_var, void* save_mean, void* save_var, void* epsilon); @@ -4401,10 +4413,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mm_out_tensor_tensor_tensor(void* out, void* self, void* mat2) { LANTERN_CHECK_LOADED void* ret = _lantern_mm_out_tensor_tensor_tensor(out, self, mat2); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_tensor_tensor)(void* sparse, void* dense); HOST_API void* lantern__sparse_mm_tensor_tensor(void* sparse, void* dense) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_tensor_tensor(sparse, dense); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_tensor_tensor_cstringview)(void* sparse, void* dense, void* reduce); + HOST_API void* lantern__sparse_mm_tensor_tensor_cstringview(void* sparse, void* dense, void* reduce) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_tensor_tensor_cstringview(sparse, dense, reduce); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_sparse_matmul_tensor_tensor)(void* self, void* other); HOST_API void* lantern__sparse_sparse_matmul_tensor_tensor(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_sparse_matmul_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_mask_helper_tensor_tensor)(void* t, void* mask_indices); - HOST_API void* lantern__sparse_mask_helper_tensor_tensor(void* t, void* mask_indices) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mask_helper_tensor_tensor(t, mask_indices); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mode_tensor_intt_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_mode_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_mode_tensor_intt_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_mode_tensor_intt_bool)(void* self, void* dim, void* keepdim); @@ -4477,6 +4489,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); HOST_API void* lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(input, weight, bias, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_stats_tensor_double)(void* input, void* eps); HOST_API void* lantern_batch_norm_stats_tensor_double(void* input, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_batch_norm_stats_tensor_double(input, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_elemt_tensor_tensor_tensor_tensor_tensor_double)(void* input, void* weight, void* bias, void* mean, void* invstd, void* eps); @@ -4715,6 +4735,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_reshape_tensor_intarrayref(void* self, void* shape) { LANTERN_CHECK_LOADED void* ret = _lantern_reshape_tensor_intarrayref(self, shape); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_reshape_tensor_intarrayref)(void* self, void* shape); HOST_API void* lantern_Tensor_reshape_tensor_intarrayref(void* self, void* shape) { void* ret = _lantern_Tensor_reshape_tensor_intarrayref(self, shape); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__reshape_copy_tensor_intarrayref)(void* self, void* size); + HOST_API void* lantern__reshape_copy_tensor_intarrayref(void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_copy_tensor_intarrayref(self, size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_tensor_intarrayref_intarrayref)(void* self, void* size, void* stride); HOST_API void* lantern__reshape_alias_tensor_intarrayref_intarrayref(void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_tensor_intarrayref_intarrayref(self, size, stride); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor__reshape_alias_tensor_intarrayref_intarrayref)(void* self, void* size, void* stride); @@ -4763,10 +4785,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_prelu_tensor_tensor(void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_prelu_tensor_tensor)(void* self, void* weight); HOST_API void* lantern_Tensor_prelu_tensor_tensor(void* self, void* weight) { void* ret = _lantern_Tensor_prelu_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); - HOST_API void* lantern_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_prelu_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); - HOST_API void* lantern_Tensor_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { void* ret = _lantern_Tensor_prelu_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__prelu_kernel_tensor_tensor)(void* self, void* weight); + HOST_API void* lantern__prelu_kernel_tensor_tensor(void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__prelu_kernel_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__prelu_kernel_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); + HOST_API void* lantern__prelu_kernel_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__prelu_kernel_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_gelu_out_tensor_tensor_cstringview)(void* out, void* self, void* approximate); HOST_API void* lantern_gelu_out_tensor_tensor_cstringview(void* out, void* self, void* approximate) { LANTERN_CHECK_LOADED void* ret = _lantern_gelu_out_tensor_tensor_cstringview(out, self, approximate); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_gelu__tensor_cstringview)(void* self, void* approximate); @@ -5003,10 +5025,16 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_squeeze_tensor_dimname(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze_tensor_dimname)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze_tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_squeeze_tensor_intarrayref(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_Tensor_squeeze_tensor_intarrayref(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor)(void* self); HOST_API void* lantern_Tensor_squeeze__tensor(void* self) { void* ret = _lantern_Tensor_squeeze__tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_intt)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze__tensor_intt(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_Tensor_squeeze__tensor_intarrayref(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_dimname)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze__tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); @@ -5361,6 +5389,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_where_tensor_scalar_tensor(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_scalar_tensor(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor_tensor_scalar)(void* condition, void* self, void* other); HOST_API void* lantern_where_tensor_tensor_scalar(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_tensor_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_where_tensor_tensor_scalar)(void* condition, void* self, void* other); + HOST_API void* lantern_Tensor_where_tensor_tensor_scalar(void* condition, void* self, void* other) { void* ret = _lantern_Tensor_where_tensor_tensor_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor_scalar_scalar)(void* condition, void* self, void* other); HOST_API void* lantern_where_tensor_scalar_scalar(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_scalar_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor)(void* condition); @@ -5471,8 +5501,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_frexp_tensor(void* self) { void* ret = _lantern_Tensor_frexp_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frexp_out_tensor_tensor_tensor)(void* mantissa, void* exponent, void* self); HOST_API void* lantern_frexp_out_tensor_tensor_tensor(void* mantissa, void* exponent, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_frexp_out_tensor_tensor_tensor(mantissa, exponent, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_tensor)(void* self); - HOST_API void* lantern_frobenius_norm_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_frobenius_norm_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_tensor_intarrayref_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_frobenius_norm_tensor_intarrayref_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_frobenius_norm_tensor_intarrayref_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* dim, void* keepdim); @@ -5551,6 +5579,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out, self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); HOST_API void* lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview)(void* self, void* other, void* reduce); + HOST_API void* lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(void* self, void* other, void* reduce) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(self, other, reduce); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool)(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask); + HOST_API void* lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(self, grad_out, weight, reduce, arg_out, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar)(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha); HOST_API void* lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out, self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_addmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); @@ -5683,20 +5715,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_unbind_tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_unbind_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor_intt)(void* self, void* sparse_dim); HOST_API void* lantern_Tensor_to_sparse_tensor_intt(void* self, void* sparse_dim) { void* ret = _lantern_Tensor_to_sparse_tensor_intt(self, sparse_dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csr_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_csr_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_csr_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csc_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_csc_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_csc_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsr_tensor_intarrayref)(void* self, void* blocksize); - HOST_API void* lantern_Tensor_to_sparse_bsr_tensor_intarrayref(void* self, void* blocksize) { void* ret = _lantern_Tensor_to_sparse_bsr_tensor_intarrayref(self, blocksize); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsc_tensor_intarrayref)(void* self, void* blocksize); - HOST_API void* lantern_Tensor_to_sparse_bsc_tensor_intarrayref(void* self, void* blocksize) { void* ret = _lantern_Tensor_to_sparse_bsc_tensor_intarrayref(self, blocksize); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt)(void* self, void* layout, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(void* self, void* layout, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(self, layout, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csr_tensor_intt)(void* self, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_csr_tensor_intt(void* self, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_csr_tensor_intt(self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csc_tensor_intt)(void* self, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_csc_tensor_intt(void* self, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_csc_tensor_intt(self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt)(void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt)(void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_mkldnn_tensor_scalartype)(void* self, void* dtype); HOST_API void* lantern_Tensor_to_mkldnn_tensor_scalartype(void* self, void* dtype) { void* ret = _lantern_Tensor_to_mkldnn_tensor_scalartype(self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* padding, void* stride, void* dilation, void* groups); - HOST_API void* lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref)(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size); + HOST_API void* lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(self, padding, stride, dilation, groups, input_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_mkldnn_backward_tensor_tensor)(void* grad, void* input); @@ -5821,8 +5853,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__local_scalar_dense_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__local_scalar_dense_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); HOST_API void* lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor)(void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias); HOST_API void* lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor(void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias) { LANTERN_CHECK_LOADED void* ret = _lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor(input_gates, hidden_gates, cx, input_bias, hidden_bias); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_backward_impl_tensor_tensor_tensor_tensor_tensor_bool)(void* grad_hy, void* grad_cy, void* cx, void* cy, void* workspace, void* has_bias); @@ -6223,8 +6255,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_diag_tensor_intt(void* self, void* diagonal) { LANTERN_CHECK_LOADED void* ret = _lantern_diag_tensor_intt(self, diagonal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_diag_tensor_intt)(void* self, void* diagonal); HOST_API void* lantern_Tensor_diag_tensor_intt(void* self, void* diagonal) { void* ret = _lantern_Tensor_diag_tensor_intt(self, diagonal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_diag_backward_tensor_intarrayref_intt)(void* grad, void* input_sizes, void* diagonal); - HOST_API void* lantern_diag_backward_tensor_intarrayref_intt(void* grad, void* input_sizes, void* diagonal) { LANTERN_CHECK_LOADED void* ret = _lantern_diag_backward_tensor_intarrayref_intt(grad, input_sizes, diagonal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_cross_out_tensor_tensor_tensor_intt)(void* out, void* self, void* other, void* dim); HOST_API void* lantern_cross_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_cross_out_tensor_tensor_tensor_intt(out, self, other, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_cross_tensor_tensor_intt)(void* self, void* other, void* dim); @@ -6521,14 +6551,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool(void* self, void* B, void* upper, void* left, void* unitriangular) { LANTERN_CHECK_LOADED void* ret = _lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool(self, B, upper, left, unitriangular); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_linalg_vander_tensor_intt)(void* x, void* N); HOST_API void* lantern_linalg_vander_tensor_intt(void* x, void* N) { LANTERN_CHECK_LOADED void* ret = _lantern_linalg_vander_tensor_intt(x, N); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_symeig_out_tensor_tensor_tensor_bool_bool)(void* e, void* V, void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_symeig_out_tensor_tensor_tensor_bool_bool(void* e, void* V, void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern_symeig_out_tensor_tensor_tensor_bool_bool(e, V, self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_symeig_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern_symeig_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_symeig_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_Tensor_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { void* ret = _lantern_Tensor_symeig_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__symeig_helper_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern__symeig_helper_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__symeig_helper_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool)(void* U, void* S, void* V, void* self, void* some, void* compute_uv); HOST_API void* lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(void* U, void* S, void* V, void* self, void* some, void* compute_uv) { LANTERN_CHECK_LOADED void* ret = _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(U, S, V, self, some, compute_uv); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_svd_tensor_bool_bool)(void* self, void* some, void* compute_uv); @@ -6819,6 +6841,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_max_tensor_tensor(void* self, void* other) { void* ret = _lantern_Tensor_max_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_max_out_tensor_tensor_tensor)(void* out, void* self, void* other); HOST_API void* lantern_max_out_tensor_tensor_tensor(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_max_out_tensor_tensor_tensor(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_max_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_max_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_minimum_tensor_tensor)(void* self, void* other); HOST_API void* lantern_minimum_tensor_tensor(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_minimum_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_minimum_tensor_tensor)(void* self, void* other); @@ -7007,6 +7031,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div__tensorlist_scalar)(void* self, void* scalar); HOST_API void* lantern__foreach_div__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_maximum_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_maximum__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_minimum_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_minimum__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_tensorlist_tensorlist_scalar)(void* self, void* other, void* alpha); HOST_API void* lantern__foreach_add_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_tensorlist_tensorlist_scalar(self, other, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add__tensorlist_tensorlist_scalar)(void* self, void* other, void* alpha); @@ -7023,6 +7063,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div__tensorlist_tensorlist)(void* self, void* other); HOST_API void* lantern__foreach_div__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_min_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_min__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_max_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_max__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_tensorlist_arrayrefscalar)(void* self, void* scalars); HOST_API void* lantern__foreach_add_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add__tensorlist_arrayrefscalar)(void* self, void* scalars); @@ -7039,6 +7095,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_mul__tensorlist_arrayrefscalar)(void* self, void* scalars); HOST_API void* lantern__foreach_mul__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_maximum_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_maximum__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_minimum_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_minimum__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_exp_tensorlist)(void* self); HOST_API void* lantern__foreach_exp_tensorlist(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_exp_tensorlist(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_zero__tensorlist)(void* self); @@ -7159,26 +7231,34 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar)(void* self, void* tensor1, void* tensor2, void* value); HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar)(void* self, void* tensor1, void* tensor2, void* value); HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_norm_tensorlist_scalar)(void* self, void* ord); HOST_API void* lantern__foreach_norm_tensorlist_scalar(void* self, void* ord) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_norm_tensorlist_scalar(self, ord); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist)(void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist)(void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_tensorlist_tensorlist_scalar)(void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp_tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_tensorlist_tensorlist_scalar(self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp__tensorlist_tensorlist_scalar)(void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp__tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp__tensorlist_tensorlist_scalar(self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_tensor_tensor_bool_bool)(void* self, void* boundaries, void* out_int32, void* right); HOST_API void* lantern_bucketize_tensor_tensor_bool_bool(void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_tensor_tensor_bool_bool(self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_out_tensor_tensor_tensor_bool_bool)(void* out, void* self, void* boundaries, void* out_int32, void* right); @@ -7187,8 +7267,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_bucketize_scalar_tensor_bool_bool(void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_scalar_tensor_bool_bool(self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor)(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__torch_cuda_cu_linker_symbol_op_tensor)(void* self); - HOST_API void* lantern__torch_cuda_cu_linker_symbol_op_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__torch_cuda_cu_linker_symbol_op_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor)(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(out, sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_tensor_scalar_bool_bool_cstringview_tensor)(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); @@ -7529,52 +7607,28 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_pad_tensor_intarrayref_cstringview_double(void* self, void* pad, void* mode, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern_pad_tensor_intarrayref_cstringview_double(self, pad, mode, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double)(void* out, void* self, void* output_size, void* align_corners, void* scales); HOST_API void* lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(void* out, void* self, void* output_size, void* align_corners, void* scales) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(out, self, output_size, align_corners, scales); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_tensor_intarrayref_bool_double)(void* self, void* output_size, void* align_corners, void* scales); @@ -8309,6 +8363,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_squeeze_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_tensor_intt)(void* self, void* dim); HOST_API void* lantern_squeeze_copy_tensor_intt(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_squeeze_copy_tensor_intarrayref(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_t_copy_tensor)(void* self); HOST_API void* lantern_t_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_tensor_intt_intt)(void* self, void* dim0, void* dim1); @@ -8333,6 +8389,12 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_row_indices_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_row_indices_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_tensor_intt)(void* self, void* dim); HOST_API void* lantern_unbind_copy_tensor_intt(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_out_tensorlist_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_out_tensorlist_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_split_copy_out_tensorlist_tensor_intt_intt)(void* out, void* self, void* split_size, void* dim); + HOST_API void* lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_copy_out_tensorlist_tensor_intt_intt(out, self, split_size, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt)(void* out, void* self, void* split_sizes, void* dim); + HOST_API void* lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out, self, split_sizes, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_view_copy_tensor_intarrayref)(void* self, void* size); HOST_API void* lantern_view_copy_tensor_intarrayref(void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_tensor_intarrayref(self, size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_view_copy_tensor_scalartype)(void* self, void* dtype); @@ -8341,88 +8403,40 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_unfold_copy_tensor_intt_intt_intt(void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_tensor_intt_intt_intt(self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_tensor)(void* self); HOST_API void* lantern_alias_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__fw_primal_copy_out_tensor_tensor_intt)(void* out, void* self, void* level); - HOST_API void* lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__fw_primal_copy_out_tensor_tensor_intt(out, self, level); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__make_dual_copy_out_tensor_tensor_tensor_intt)(void* out, void* primal, void* tangent, void* level); - HOST_API void* lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out, primal, tangent, level); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_as_real_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_real_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_as_complex_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_complex_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__conj_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__conj_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__neg_view_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__neg_view_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt)(void* out, void* self, void* size, void* stride, void* storage_offset); - HOST_API void* lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_CHECK_LOADED void* ret = _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out, self, size, stride, storage_offset); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); - HOST_API void* lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); - HOST_API void* lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_CHECK_LOADED void* ret = _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out, self, offset, dim1, dim2); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_expand_copy_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* size, void* implicit); - HOST_API void* lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_CHECK_LOADED void* ret = _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out, self, size, implicit); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_permute_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dims); - HOST_API void* lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_CHECK_LOADED void* ret = _lantern_permute_copy_out_tensor_tensor_intarrayref(out, self, dims); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref)(void* out, void* self, void* size, void* stride); - HOST_API void* lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out, self, size, stride); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_select_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim, void* index); - HOST_API void* lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_copy_out_tensor_tensor_intt_intt(out, self, dim, index); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_detach_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_detach_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt)(void* out, void* self, void* dim, void* start, void* end, void* step); - HOST_API void* lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out, self, dim, start, end, step); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_split_copy_out_tensorlist_tensor_intt_intt)(void* out, void* self, void* split_size, void* dim); - HOST_API void* lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_copy_out_tensorlist_tensor_intt_intt(out, self, split_size, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt)(void* out, void* self, void* split_sizes, void* dim); - HOST_API void* lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out, self, split_sizes, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_t_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim0, void* dim1); - HOST_API void* lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_CHECK_LOADED void* ret = _lantern_transpose_copy_out_tensor_tensor_intt_intt(out, self, dim0, dim1); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unsqueeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unsqueeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__values_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_values_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_crow_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_crow_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_col_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_col_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_out_tensorlist_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_out_tensorlist_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); - HOST_API void* lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); - HOST_API void* lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* dimension, void* size, void* step); - HOST_API void* lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out, self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_alias_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref)(void* self, void* padding, void* output_size); HOST_API void* lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(void* self, void* padding, void* output_size) { void* ret = _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(self, padding, output_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_softmax_with_shape_tensor_tensor)(void* self, void* query); HOST_API void* lantern__nested_tensor_softmax_with_shape_tensor_tensor(void* self, void* query) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_softmax_with_shape_tensor_tensor(self, query); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double)(void* self, void* weight, void* bias, void* eps); - HOST_API void* lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(void* self, void* weight, void* bias, void* eps) { void* ret = _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(self, weight, bias, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt)(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type); HOST_API void* lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type); HOST_API void* lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal); + HOST_API void* lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(query, key, value, attn_mask, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); HOST_API void* lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); - HOST_API void* lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); - HOST_API void* lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal); + HOST_API void* lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(query, key, value, attn_mask, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask); + HOST_API void* lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask); + HOST_API void* lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(query, key, value, dropout_p, is_causal, return_debug_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt)(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset); + HOST_API void* lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool)(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal); + HOST_API void* lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(query, key, value, compute_log_sumexp, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs); + HOST_API void* lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool)(void* query, void* key, void* value, void* is_causal); + HOST_API void* lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(void* query, void* key, void* value, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(query, key, value, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool)(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask); + HOST_API void* lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt)(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset); + HOST_API void* lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool)(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal); + HOST_API void* lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal) { LANTERN_CHECK_LOADED void* ret = _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs); + HOST_API void* lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_CHECK_LOADED void* ret = _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double)(void* q, void* k, void* v, void* dropout_p); HOST_API void* lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(void* q, void* k, void* v, void* dropout_p) { LANTERN_CHECK_LOADED void* ret = _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(q, k, v, dropout_p); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask); @@ -8431,8 +8445,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_special_airy_ai_tensor(void* x) { LANTERN_CHECK_LOADED void* ret = _lantern_special_airy_ai_tensor(x); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_special_airy_ai_out_tensor_tensor)(void* out, void* x); HOST_API void* lantern_special_airy_ai_out_tensor_tensor(void* out, void* x) { LANTERN_CHECK_LOADED void* ret = _lantern_special_airy_ai_out_tensor_tensor(out, x); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool)(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal); - HOST_API void* lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor)(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value); HOST_API void* lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, incr_key, incr_value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* incr_key, void* incr_value, void* need_weights, void* average_attn_weights); @@ -8629,6 +8641,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foobar_tensor_bool_bool_bool(void* self, void* arg1, void* arg2, void* arg3) { LANTERN_CHECK_LOADED void* ret = _lantern__foobar_tensor_bool_bool_bool(self, arg1, arg2, arg3); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); HOST_API void* lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt)(void* out, void* self, void* other, void* self_num_batch_dims); HOST_API void* lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* self_num_batch_dims) { LANTERN_CHECK_LOADED void* ret = _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(out, self, other, self_num_batch_dims); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__cudnn_ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* deterministic, void* zero_infinity); @@ -8729,6 +8743,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* self, void* grid, void* grad_output) { LANTERN_CHECK_LOADED void* ret = _lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor(out0, out1, self, grid, grad_output); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity); HOST_API void* lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity); + HOST_API void* lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool)(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity); HOST_API void* lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(out, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_diag_embed_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); @@ -8855,10 +8871,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__aminmax_out_tensor_tensor_tensor(void* out0, void* out1, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__aminmax_out_tensor_tensor_tensor(out0, out1, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__aminmax_out_tensor_tensor_tensor_intt_bool)(void* out0, void* out1, void* self, void* dim, void* keepdim); HOST_API void* lantern__aminmax_out_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern__aminmax_out_tensor_tensor_tensor_intt_bool(out0, out1, self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); + HOST_API void* lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* output, void* input, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); @@ -8881,6 +8895,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(void* out0, void* out1, void* out2, void* self, void* grad_output, void* weight, void* padding, void* stride, void* dilation, void* groups, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(out0, out1, out2, self, grad_output, weight, padding, stride, dilation, groups, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, weight, bias, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train); + HOST_API void* lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor)(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace); + HOST_API void* lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon); HOST_API void* lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out0, out1, out2, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double)(void* out0, void* out1, void* out2, void* input, void* grad_output, void* weight, void* running_mean, void* running_var, void* save_mean, void* save_var, void* epsilon); @@ -8897,10 +8915,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight, void* weight_stride0, void* weight_buf, void* hx, void* cx, void* output, void* grad_output, void* grad_hy, void* grad_cy, void* mode, void* hidden_size, void* num_layers, void* batch_first, void* dropout, void* train, void* bidirectional, void* batch_sizes, void* dropout_state, void* reserve, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool(out0, out1, out2, out3, input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor)(void* out, void* self, void* other); HOST_API void* lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(out, self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_mask_helper_out_tensor_tensor_tensor)(void* out, void* t, void* mask_indices); - HOST_API void* lantern__sparse_mask_helper_out_tensor_tensor_tensor(void* out, void* t, void* mask_indices) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mask_helper_out_tensor_tensor_tensor(out, t, mask_indices); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mul_out_tensor_tensor_scalar)(void* out, void* self, void* other); HOST_API void* lantern_mul_out_tensor_tensor_scalar(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_mul_out_tensor_tensor_scalar(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_stats_out_tensor_tensor_tensor_double)(void* out0, void* out1, void* input, void* eps); HOST_API void* lantern_batch_norm_stats_out_tensor_tensor_tensor_double(void* out0, void* out1, void* input, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_batch_norm_stats_out_tensor_tensor_tensor_double(out0, out1, input, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_gather_stats_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_intt)(void* out0, void* out1, void* input, void* mean, void* invstd, void* running_mean, void* running_var, void* momentum, void* eps, void* count); @@ -8965,10 +8983,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__mkldnn_reshape_out_tensor_tensor_intarrayref(void* out, void* self, void* shape) { LANTERN_CHECK_LOADED void* ret = _lantern__mkldnn_reshape_out_tensor_tensor_intarrayref(out, self, shape); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_relu_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_relu_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_relu_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_out_tensor_tensor_tensor)(void* out, void* self, void* weight); - HOST_API void* lantern_prelu_out_tensor_tensor_tensor(void* out, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_out_tensor_tensor_tensor(out, self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor)(void* out0, void* out1, void* grad_output, void* self, void* weight); - HOST_API void* lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(out0, out1, grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt)(void* out, void* grad_output, void* input_sizes, void* dim, void* index); HOST_API void* lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(void* out, void* grad_output, void* input_sizes, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(out, grad_output, input_sizes, dim, index); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_celu_out_tensor_tensor_scalar)(void* out, void* self, void* alpha); @@ -9131,20 +9145,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_copy_sparse_to_sparse_tensor_tensor_bool(void* self, void* src, void* non_blocking) { LANTERN_CHECK_LOADED void* ret = _lantern_copy_sparse_to_sparse_tensor_tensor_bool(self, src, non_blocking); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor_intt)(void* out, void* self, void* sparse_dim); HOST_API void* lantern_to_sparse_out_tensor_tensor_intt(void* out, void* self, void* sparse_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor_intt(out, self, sparse_dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csr_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_csr_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csr_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csc_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_csc_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csc_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref)(void* out, void* self, void* blocksize); - HOST_API void* lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(out, self, blocksize); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref)(void* out, void* self, void* blocksize); - HOST_API void* lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(out, self, blocksize); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt)(void* out, void* self, void* layout, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(void* out, void* self, void* layout, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(out, self, layout, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csr_out_tensor_tensor_intt)(void* out, void* self, void* dense_dim); + HOST_API void* lantern_to_sparse_csr_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csr_out_tensor_tensor_intt(out, self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csc_out_tensor_tensor_intt)(void* out, void* self, void* dense_dim); + HOST_API void* lantern_to_sparse_csc_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csc_out_tensor_tensor_intt(out, self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt)(void* out, void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(out, self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt)(void* out, void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(out, self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_mkldnn_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); HOST_API void* lantern_to_mkldnn_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_to_mkldnn_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups); - HOST_API void* lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size); + HOST_API void* lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(out, self, padding, stride, dilation, groups, input_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_quantize_per_tensor_dynamic_out_tensor_tensor_scalartype_bool)(void* out, void* self, void* dtype, void* reduce_range); @@ -9187,10 +9201,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool(void* self, void* observer_on, void* fake_quant_on, void* running_min, void* running_max, void* scale, void* zero_point, void* averaging_const, void* quant_min, void* quant_max, void* ch_axis, void* per_row_fake_quant, void* symmetric_quant) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__to_copy_out_tensor_tensor_bool_memoryformat)(void* out, void* self, void* non_blocking, void* memory_format); HOST_API void* lantern__to_copy_out_tensor_tensor_bool_memoryformat(void* out, void* self, void* non_blocking, void* memory_format) { LANTERN_CHECK_LOADED void* ret = _lantern__to_copy_out_tensor_tensor_bool_memoryformat(out, self, non_blocking, memory_format); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor)(void* out0, void* out1, void* out2, void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias); HOST_API void* lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* out2, void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias) { LANTERN_CHECK_LOADED void* ret = _lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(out0, out1, out2, input_gates, hidden_gates, cx, input_bias, hidden_bias); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_backward_impl_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool)(void* out0, void* out1, void* out2, void* grad_hy, void* grad_cy, void* cx, void* cy, void* workspace, void* has_bias); @@ -9293,8 +9307,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_triu_indices_out_tensor_intt_intt_intt(void* out, void* row, void* col, void* offset) { LANTERN_CHECK_LOADED void* ret = _lantern_triu_indices_out_tensor_intt_intt_intt(out, row, col, offset); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_trace_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_trace_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_trace_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool)(void* out0, void* out1, void* self, void* eigenvectors, void* upper); - HOST_API void* lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(void* out0, void* out1, void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(out0, out1, self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool)(void* out, void* self, void* A, void* upper); HOST_API void* lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(void* out, void* self, void* A, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(out, self, A, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_dist_out_tensor_tensor_tensor_scalar)(void* out, void* self, void* other, void* p); @@ -9329,6 +9341,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* other, void* alpha); HOST_API void* lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(out, self, other, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* other, void* alpha); @@ -9337,6 +9357,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); HOST_API void* lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_sub_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); @@ -9345,6 +9373,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_exp_out_tensorlist_tensorlist)(void* out, void* self); HOST_API void* lantern__foreach_exp_out_tensorlist_tensorlist(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_exp_out_tensorlist_tensorlist(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_zero_out_tensorlist_tensorlist)(void* out, void* self); @@ -9411,18 +9447,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar(out, self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); - HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); - HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_norm_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* ord); HOST_API void* lantern__foreach_norm_out_tensorlist_tensorlist_scalar(void* out, void* self, void* ord) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_norm_out_tensorlist_tensorlist_scalar(out, self, ord); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(void* out, void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(out, self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(out, self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_out_tensor_scalar_tensor_bool_bool)(void* out, void* self, void* boundaries, void* out_int32, void* right); HOST_API void* lantern_bucketize_out_tensor_scalar_tensor_bool_bool(void* out, void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_out_tensor_scalar_tensor_bool_bool(out, self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor)(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor(out, sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_glu_jvp_out_tensor_tensor_tensor_tensor_intt)(void* out, void* glu, void* x, void* dx, void* dim); @@ -9443,54 +9481,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref(void* out, void* self, void* output_size) { LANTERN_CHECK_LOADED void* ret = _lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref(out, self, output_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor)(void* out, void* grad_output, void* self); HOST_API void* lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(void* out, void* grad_output, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(out, grad_output, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool)(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask); HOST_API void* lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref)(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation); @@ -9521,14 +9511,74 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(void* out, void* grad, void* output, void* data, void* reduce, void* lengths, void* offsets, void* axis, void* initial) { LANTERN_CHECK_LOADED void* ret = _lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(out, grad, output, data, reduce, lengths, offsets, axis, initial); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool)(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory); HOST_API void* lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(out, list, dtype, layout, device, pin_memory); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fw_primal_copy_out_tensor_tensor_intt)(void* out, void* self, void* level); + HOST_API void* lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__fw_primal_copy_out_tensor_tensor_intt(out, self, level); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__make_dual_copy_out_tensor_tensor_tensor_intt)(void* out, void* primal, void* tangent, void* level); + HOST_API void* lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out, primal, tangent, level); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_as_real_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_real_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_as_complex_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_complex_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__conj_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__conj_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__neg_view_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__neg_view_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt)(void* out, void* self, void* size, void* stride, void* storage_offset); + HOST_API void* lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_CHECK_LOADED void* ret = _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out, self, size, stride, storage_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); + HOST_API void* lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); + HOST_API void* lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_CHECK_LOADED void* ret = _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out, self, offset, dim1, dim2); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_expand_copy_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* size, void* implicit); + HOST_API void* lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_CHECK_LOADED void* ret = _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out, self, size, implicit); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_permute_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dims); + HOST_API void* lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_CHECK_LOADED void* ret = _lantern_permute_copy_out_tensor_tensor_intarrayref(out, self, dims); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref)(void* out, void* self, void* size, void* stride); + HOST_API void* lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out, self, size, stride); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_select_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim, void* index); + HOST_API void* lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_copy_out_tensor_tensor_intt_intt(out, self, dim, index); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_detach_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_detach_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt)(void* out, void* self, void* dim, void* start, void* end, void* step); + HOST_API void* lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out, self, dim, start, end, step); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dim); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intarrayref(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_t_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim0, void* dim1); + HOST_API void* lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_CHECK_LOADED void* ret = _lantern_transpose_copy_out_tensor_tensor_intt_intt(out, self, dim0, dim1); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unsqueeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unsqueeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__values_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_values_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_crow_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_crow_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_col_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_col_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_ccol_indices_copy_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_ccol_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_ccol_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_row_indices_copy_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_row_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_row_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); + HOST_API void* lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); + HOST_API void* lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* dimension, void* size, void* step); + HOST_API void* lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out, self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_alias_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref)(void* out, void* self, void* padding, void* output_size); HOST_API void* lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(void* out, void* self, void* padding, void* output_size) { LANTERN_CHECK_LOADED void* ret = _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(out, self, padding, output_size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double)(void* out, void* self, void* weight, void* bias, void* eps); - HOST_API void* lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(void* out, void* self, void* weight, void* bias, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(out, self, weight, bias, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt)(void* out, void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type); HOST_API void* lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* out, void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(out, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_multi_head_attention_out_tensor_tensor_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt)(void* out0, void* out1, void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type); @@ -9547,6 +9597,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); HOST_API void* lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } /* Autogen Headers -- End */ #ifdef __cplusplus @@ -10309,6 +10363,11 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_addr_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_affine_grid_generator_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_affine_grid_generator_backward_tensor_intarrayref_bool) + LOAD_SYMBOL(_lantern__is_all_true_tensor) + LOAD_SYMBOL(_lantern_Tensor__is_all_true_tensor) + LOAD_SYMBOL(_lantern__is_any_true_tensor) + LOAD_SYMBOL(_lantern_Tensor__is_any_true_tensor) + LOAD_SYMBOL(_lantern__test_check_tensor_tensor) LOAD_SYMBOL(_lantern_all_tensor_intt_bool) LOAD_SYMBOL(_lantern_Tensor_all_tensor_intt_bool) LOAD_SYMBOL(_lantern_all_out_tensor_tensor_intt_bool) @@ -11016,8 +11075,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_max_pool1d_with_indices_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) + LOAD_SYMBOL(_lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool3d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) @@ -11064,6 +11122,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__mps_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool) LOAD_SYMBOL(_lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor) LOAD_SYMBOL(_lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_miopen_batch_norm_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_miopen_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_bool_bool) @@ -11077,8 +11137,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_mm_tensor_tensor) LOAD_SYMBOL(_lantern_mm_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__sparse_mm_tensor_tensor) + LOAD_SYMBOL(_lantern__sparse_mm_tensor_tensor_cstringview) LOAD_SYMBOL(_lantern__sparse_sparse_matmul_tensor_tensor) - LOAD_SYMBOL(_lantern__sparse_mask_helper_tensor_tensor) LOAD_SYMBOL(_lantern_mode_tensor_intt_bool) LOAD_SYMBOL(_lantern_Tensor_mode_tensor_intt_bool) LOAD_SYMBOL(_lantern_mode_out_tensor_tensor_tensor_intt_bool) @@ -11115,6 +11175,10 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_narrow_tensor_intt_tensor_intt) LOAD_SYMBOL(_lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_batch_norm_stats_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_elemt_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_elemt_out_tensor_tensor_tensor_tensor_tensor_tensor_double) @@ -11234,6 +11298,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_repeat_interleave_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_reshape_tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_reshape_tensor_intarrayref) + LOAD_SYMBOL(_lantern__reshape_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern__reshape_alias_tensor_intarrayref_intarrayref) LOAD_SYMBOL(_lantern_Tensor__reshape_alias_tensor_intarrayref_intarrayref) LOAD_SYMBOL(_lantern__mkldnn_reshape_tensor_intarrayref) @@ -11258,8 +11323,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_relu6__tensor) LOAD_SYMBOL(_lantern_prelu_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_prelu_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_backward_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_Tensor_prelu_backward_tensor_tensor_tensor) + LOAD_SYMBOL(_lantern__prelu_kernel_tensor_tensor) + LOAD_SYMBOL(_lantern__prelu_kernel_backward_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_gelu_out_tensor_tensor_cstringview) LOAD_SYMBOL(_lantern_gelu__tensor_cstringview) LOAD_SYMBOL(_lantern_gelu_tensor_cstringview) @@ -11378,8 +11443,11 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_intt) LOAD_SYMBOL(_lantern_squeeze_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_dimname) + LOAD_SYMBOL(_lantern_squeeze_tensor_intarrayref) + LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_dimname) LOAD_SYMBOL(_lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_Tensor_sspaddmm_tensor_tensor_tensor_scalar_scalar) @@ -11557,6 +11625,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_where_out_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_where_tensor_scalar_tensor) LOAD_SYMBOL(_lantern_where_tensor_tensor_scalar) + LOAD_SYMBOL(_lantern_Tensor_where_tensor_tensor_scalar) LOAD_SYMBOL(_lantern_where_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_where_tensor) LOAD_SYMBOL(_lantern_norm_except_dim_tensor_intt_intt) @@ -11612,7 +11681,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_frexp_tensor) LOAD_SYMBOL(_lantern_Tensor_frexp_tensor) LOAD_SYMBOL(_lantern_frexp_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_frobenius_norm_tensor) LOAD_SYMBOL(_lantern_frobenius_norm_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_frobenius_norm_out_tensor_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_nuclear_norm_tensor_bool) @@ -11652,6 +11720,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__sparse_addmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar) + LOAD_SYMBOL(_lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview) + LOAD_SYMBOL(_lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool) LOAD_SYMBOL(_lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_addmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_Tensor_addmm_tensor_tensor_tensor_scalar_scalar) @@ -11718,13 +11788,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_unbind_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_unbind_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor_intt) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_csr_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_csc_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsr_tensor_intarrayref) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsc_tensor_intarrayref) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_csr_tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_csc_tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_Tensor_to_mkldnn_tensor_scalartype) - LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref) LOAD_SYMBOL(_lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_to_mkldnn_backward_tensor_tensor) LOAD_SYMBOL(_lantern_quantize_per_tensor_dynamic_tensor_scalartype_bool) @@ -11787,7 +11857,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_promote_types_scalartype_scalartype) LOAD_SYMBOL(_lantern__local_scalar_dense_tensor) LOAD_SYMBOL(_lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) - LOAD_SYMBOL(_lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_impl_tensor_tensor_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_tensor_tensor_tensor_tensor_tensor_bool) @@ -11988,7 +12058,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_diag_out_tensor_tensor_intt) LOAD_SYMBOL(_lantern_diag_tensor_intt) LOAD_SYMBOL(_lantern_Tensor_diag_tensor_intt) - LOAD_SYMBOL(_lantern_diag_backward_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_cross_out_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern_cross_tensor_tensor_intt) LOAD_SYMBOL(_lantern_Tensor_cross_tensor_tensor_intt) @@ -12137,10 +12206,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_linalg_solve_triangular_out_tensor_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern_linalg_vander_tensor_intt) - LOAD_SYMBOL(_lantern_symeig_out_tensor_tensor_tensor_bool_bool) - LOAD_SYMBOL(_lantern_symeig_tensor_bool_bool) - LOAD_SYMBOL(_lantern_Tensor_symeig_tensor_bool_bool) - LOAD_SYMBOL(_lantern__symeig_helper_tensor_bool_bool) LOAD_SYMBOL(_lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_svd_tensor_bool_bool) LOAD_SYMBOL(_lantern_Tensor_svd_tensor_bool_bool) @@ -12286,6 +12351,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_max_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_max_tensor_tensor) LOAD_SYMBOL(_lantern_max_out_tensor_tensor_tensor) + LOAD_SYMBOL(_lantern_max_out_tensor_tensor) LOAD_SYMBOL(_lantern_minimum_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_minimum_tensor_tensor) LOAD_SYMBOL(_lantern_minimum_out_tensor_tensor_tensor) @@ -12380,6 +12446,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add__tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_sub_tensorlist_tensorlist_scalar) @@ -12388,6 +12462,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_add_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_add__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_sub_tensorlist_arrayrefscalar) @@ -12396,6 +12478,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_div__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_exp_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero__tensorlist) LOAD_SYMBOL(_lantern__foreach_exp__tensorlist) @@ -12456,21 +12546,24 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar) - LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_norm_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp__tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp__tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern_bucketize_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_bucketize_out_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_bucketize_scalar_tensor_bool_bool) LOAD_SYMBOL(_lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor) - LOAD_SYMBOL(_lantern__torch_cuda_cu_linker_symbol_op_tensor) LOAD_SYMBOL(_lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern_searchsorted_tensor_scalar_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern__convert_indices_from_coo_to_csr_tensor_intt_bool) @@ -12641,29 +12734,17 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__pad_enum_tensor_intarrayref_intt_double) LOAD_SYMBOL(_lantern_pad_tensor_intarrayref_cstringview_double) LOAD_SYMBOL(_lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double) LOAD_SYMBOL(_lantern_upsample_linear1d_tensor_intarrayref_bool_double) LOAD_SYMBOL(_lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_double) @@ -13031,6 +13112,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_split_with_sizes_copy_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_squeeze_copy_tensor) LOAD_SYMBOL(_lantern_squeeze_copy_tensor_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern_t_copy_tensor) LOAD_SYMBOL(_lantern_transpose_copy_tensor_intt_intt) LOAD_SYMBOL(_lantern_unsqueeze_copy_tensor_intt) @@ -13043,56 +13125,34 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_ccol_indices_copy_tensor) LOAD_SYMBOL(_lantern_row_indices_copy_tensor) LOAD_SYMBOL(_lantern_unbind_copy_tensor_intt) + LOAD_SYMBOL(_lantern_unbind_copy_out_tensorlist_tensor_intt) + LOAD_SYMBOL(_lantern_split_copy_out_tensorlist_tensor_intt_intt) + LOAD_SYMBOL(_lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_view_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern_view_copy_tensor_scalartype) LOAD_SYMBOL(_lantern_unfold_copy_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_alias_copy_tensor) - LOAD_SYMBOL(_lantern__fw_primal_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern__make_dual_copy_out_tensor_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_view_as_real_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_view_as_complex_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__conj_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__neg_view_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt) - LOAD_SYMBOL(_lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt) - LOAD_SYMBOL(_lantern_expand_copy_out_tensor_tensor_intarrayref_bool) - LOAD_SYMBOL(_lantern_permute_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref) - LOAD_SYMBOL(_lantern_select_copy_out_tensor_tensor_intt_intt) - LOAD_SYMBOL(_lantern_detach_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt) - LOAD_SYMBOL(_lantern_split_copy_out_tensorlist_tensor_intt_intt) - LOAD_SYMBOL(_lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt) - LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_t_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_transpose_copy_out_tensor_tensor_intt_intt) - LOAD_SYMBOL(_lantern_unsqueeze_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern__indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__values_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_values_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_crow_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_col_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_unbind_copy_out_tensorlist_tensor_intt) - LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_scalartype) - LOAD_SYMBOL(_lantern_unfold_copy_out_tensor_tensor_intt_intt_intt) - LOAD_SYMBOL(_lantern_alias_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_to_padded_tensor_tensor_double_intarrayref) LOAD_SYMBOL(_lantern__nested_tensor_softmax_with_shape_tensor_tensor) - LOAD_SYMBOL(_lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt) + LOAD_SYMBOL(_lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool) LOAD_SYMBOL(_lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool) - LOAD_SYMBOL(_lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool) - LOAD_SYMBOL(_lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool) + LOAD_SYMBOL(_lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor) + LOAD_SYMBOL(_lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt) + LOAD_SYMBOL(_lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) + LOAD_SYMBOL(_lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool) + LOAD_SYMBOL(_lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool) + LOAD_SYMBOL(_lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt) + LOAD_SYMBOL(_lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool) + LOAD_SYMBOL(_lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_special_airy_ai_tensor) LOAD_SYMBOL(_lantern_special_airy_ai_out_tensor_tensor) - LOAD_SYMBOL(_lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool) LOAD_SYMBOL(_lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_special_bessel_j0_tensor) @@ -13191,6 +13251,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_special_spherical_bessel_j0_out_tensor_tensor) LOAD_SYMBOL(_lantern__foobar_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) LOAD_SYMBOL(_lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__cudnn_ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool_bool) LOAD_SYMBOL(_lantern__cudnn_rnn_flatten_weight_out_tensor_tensorlist_intt_intt_intt_intt_intt_intt_bool_bool) @@ -13241,6 +13302,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_cudnn_grid_sampler_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool) + LOAD_SYMBOL(_lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool) LOAD_SYMBOL(_lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool) LOAD_SYMBOL(_lantern_diag_embed_out_tensor_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_diagonal_backward_out_tensor_tensor_intarrayref_intt_intt_intt) @@ -13304,8 +13366,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_matmul_backward_out_tensor_tensor_tensor_tensor_tensor_stdarraybool) LOAD_SYMBOL(_lantern__aminmax_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__aminmax_out_tensor_tensor_tensor_intt_bool) - LOAD_SYMBOL(_lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) + LOAD_SYMBOL(_lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool3d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) @@ -13317,6 +13378,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__mps_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool) LOAD_SYMBOL(_lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor) LOAD_SYMBOL(_lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_miopen_batch_norm_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_miopen_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_bool_bool) @@ -13325,8 +13388,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_miopen_rnn_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_intt_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor) LOAD_SYMBOL(_lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool) LOAD_SYMBOL(_lantern__sparse_sparse_matmul_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern__sparse_mask_helper_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_mul_out_tensor_tensor_scalar) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_batch_norm_stats_out_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_gather_stats_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_intt) LOAD_SYMBOL(_lantern_batch_norm_gather_stats_with_counts_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_tensor) @@ -13359,8 +13422,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_repeat_interleave_out_tensor_tensor_intt) LOAD_SYMBOL(_lantern__mkldnn_reshape_out_tensor_tensor_intarrayref) LOAD_SYMBOL(_lantern_relu_out_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt) LOAD_SYMBOL(_lantern_celu_out_tensor_tensor_scalar) LOAD_SYMBOL(_lantern_slice_backward_out_tensor_tensor_intarrayref_intt_intt_intt_intt) @@ -13442,13 +13503,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_copy_sparse_to_sparse_out_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern_copy_sparse_to_sparse_tensor_tensor_bool) LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_csr_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_csc_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_bsr_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_to_sparse_bsc_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt) + LOAD_SYMBOL(_lantern_to_sparse_csr_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_to_sparse_csc_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt) + LOAD_SYMBOL(_lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_to_mkldnn_out_tensor_tensor_scalartype) - LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref) LOAD_SYMBOL(_lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_quantize_per_tensor_dynamic_out_tensor_tensor_scalartype_bool) LOAD_SYMBOL(_lantern_quantize_per_tensor_out_tensor_tensor_double_intt_scalartype) @@ -13470,8 +13531,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__fused_moving_avg_obs_fq_helper_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool) LOAD_SYMBOL(_lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool) LOAD_SYMBOL(_lantern__to_copy_out_tensor_tensor_bool_memoryformat) - LOAD_SYMBOL(_lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) - LOAD_SYMBOL(_lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_impl_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern__thnn_fused_gru_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor) @@ -13523,7 +13584,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_tril_indices_out_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_triu_indices_out_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_trace_out_tensor_tensor) - LOAD_SYMBOL(_lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern_dist_out_tensor_tensor_tensor_scalar) LOAD_SYMBOL(_lantern__histogramdd_bin_edges_out_tensorlist_tensor_intarrayref_arrayrefdouble_tensor_bool) @@ -13541,14 +13601,26 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_exp_out_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero_out_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero_tensorlist) @@ -13582,12 +13654,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar) - LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_norm_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern_bucketize_out_tensor_scalar_tensor_bool_bool) - LOAD_SYMBOL(_lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor) LOAD_SYMBOL(_lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern_glu_jvp_out_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern_glu_backward_jvp_out_tensor_tensor_tensor_tensor_tensor_tensor_intt) @@ -13598,30 +13671,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__adaptive_avg_pool2d_backward_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref) LOAD_SYMBOL(_lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool) LOAD_SYMBOL(_lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref) LOAD_SYMBOL(_lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref) @@ -13637,10 +13686,40 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar) LOAD_SYMBOL(_lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar) LOAD_SYMBOL(_lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool) + LOAD_SYMBOL(_lantern__fw_primal_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern__make_dual_copy_out_tensor_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_view_as_real_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_view_as_complex_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__conj_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__neg_view_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt) + LOAD_SYMBOL(_lantern_expand_copy_out_tensor_tensor_intarrayref_bool) + LOAD_SYMBOL(_lantern_permute_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref) + LOAD_SYMBOL(_lantern_select_copy_out_tensor_tensor_intt_intt) + LOAD_SYMBOL(_lantern_detach_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_t_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_transpose_copy_out_tensor_tensor_intt_intt) + LOAD_SYMBOL(_lantern_unsqueeze_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern__indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__values_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_values_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_crow_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_col_indices_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_ccol_indices_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_row_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_scalartype) + LOAD_SYMBOL(_lantern_unfold_copy_out_tensor_tensor_intt_intt_intt) + LOAD_SYMBOL(_lantern_alias_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref) - LOAD_SYMBOL(_lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__native_multi_head_attention_out_tensor_tensor_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt) LOAD_SYMBOL(_lantern__triton_scaled_dot_attention_out_tensor_tensor_tensor_tensor_double) @@ -13650,6 +13729,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foobar_out_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) LOAD_SYMBOL(_lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) /* Autogen Symbols -- End */ return true; diff --git a/src/lantern/src/Indexing.cpp b/src/lantern/src/Indexing.cpp index b3bae84bb4..be2cdf458e 100644 --- a/src/lantern/src/Indexing.cpp +++ b/src/lantern/src/Indexing.cpp @@ -66,6 +66,15 @@ void _lantern_TensorIndex_append_int64(void *self, int64_t x) { LANTERN_FUNCTION_END_VOID } +c10::optional symint_from_optional_int (c10::optional x) { + if (x == c10::nullopt) { + return c10::nullopt; + } + else { + return c10::SymInt(*x); + } +} + void *_lantern_Slice(void *start, void *end, void *step) { LANTERN_FUNCTION_START auto start_ = from_raw::optional::int64_t(start); @@ -83,7 +92,10 @@ void *_lantern_Slice(void *start, void *end, void *step) { step_ = None; } - auto out = torch::indexing::Slice(start_, end_, step_); + + + + auto out = torch::indexing::Slice(symint_from_optional_int(start_), symint_from_optional_int(end_), symint_from_optional_int(step_)); return make_ptr(out); LANTERN_FUNCTION_END } diff --git a/src/lantern/src/Pickler.cpp b/src/lantern/src/Pickler.cpp index 3ec4d43c2b..e4bf753b74 100644 --- a/src/lantern/src/Pickler.cpp +++ b/src/lantern/src/Pickler.cpp @@ -108,7 +108,7 @@ class DeserializationStorageContext; // deleted at some point, the Pickler doesn't produce it and it's only around to // support models saved before 1.1 class LANTERN_API LanternUnpickler { - TH_DISALLOW_COPY_AND_ASSIGN(LanternUnpickler); + AT_DISALLOW_COPY_AND_ASSIGN(LanternUnpickler); using TypeParserT = c10::TypePtr (*)(const std::string&); diff --git a/src/lantern/src/Tensor.cpp b/src/lantern/src/Tensor.cpp index 9facf5f23f..dbd4e9b0c6 100644 --- a/src/lantern/src/Tensor.cpp +++ b/src/lantern/src/Tensor.cpp @@ -384,8 +384,8 @@ void _lantern_tensor_set_pyobj(void *x, void *ptr) { LANTERN_FUNCTION_START PyObject *ptr_ = reinterpret_cast(ptr); auto t = from_raw::Tensor(x); - t.unsafeGetTensorImpl()->init_pyobj( - &lantern_interpreter, ptr_, + t.unsafeGetTensorImpl()->pyobj_slot()->init_pyobj( + nullptr, ptr_, c10::impl::PyInterpreterStatus::DEFINITELY_UNINITIALIZED); LANTERN_FUNCTION_END_VOID } @@ -393,7 +393,7 @@ void _lantern_tensor_set_pyobj(void *x, void *ptr) { void *_lantern_tensor_get_pyobj(void *x) { LANTERN_FUNCTION_START auto t = from_raw::Tensor(x); - auto pyobj = t.unsafeGetTensorImpl()->check_pyobj(&lantern_interpreter); + auto pyobj = t.unsafeGetTensorImpl()->pyobj_slot()->check_pyobj(&lantern_interpreter); if (pyobj.has_value()) { return (void *)pyobj.value(); } else { diff --git a/src/lantern/src/lantern.cpp b/src/lantern/src/lantern.cpp index 04194b7b7f..72edf9ce88 100644 --- a/src/lantern/src/lantern.cpp +++ b/src/lantern/src/lantern.cpp @@ -1119,6 +1119,46 @@ void* _lantern_affine_grid_generator_backward_tensor_intarrayref_bool(void* grad LANTERN_FUNCTION_END } +void* _lantern__is_all_true_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_is_all_true( + from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + +void* _lantern_Tensor__is_all_true_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(self)._is_all_true( + )); + LANTERN_FUNCTION_END +} + +void* _lantern__is_any_true_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_is_any_true( + from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + +void* _lantern_Tensor__is_any_true_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(self)._is_any_true( + )); + LANTERN_FUNCTION_END +} + +void* _lantern__test_check_tensor_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_test_check_tensor( + from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + void* _lantern_all_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_FUNCTION_START @@ -6791,18 +6831,10 @@ void* _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref LANTERN_FUNCTION_END } -void* _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_mps_max_pool2d( - from_raw::Tensor(self), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation), from_raw::bool_t(ceil_mode))); - LANTERN_FUNCTION_END -} - -void* _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) +void* _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::mps_max_pool2d_backward( + return make_raw::Tensor(torch::max_pool2d_backward( from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation), from_raw::bool_t(ceil_mode))); LANTERN_FUNCTION_END } @@ -7175,6 +7207,22 @@ void* _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_i LANTERN_FUNCTION_END } +void* _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::mkldnn_rnn_layer( + from_raw::Tensor(input), from_raw::Tensor(weight0), from_raw::Tensor(weight1), from_raw::Tensor(weight2), from_raw::Tensor(weight3), from_raw::Tensor(hx_), from_raw::Tensor(cx_), from_raw::bool_t(reverse), from_raw::IntArrayRef(batch_sizes), from_raw::int64_t(mode), from_raw::int64_t(hidden_size), from_raw::int64_t(num_layers), from_raw::bool_t(has_biases), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first), from_raw::bool_t(train))); + LANTERN_FUNCTION_END +} + +void* _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::mkldnn_rnn_layer_backward( + from_raw::Tensor(input), from_raw::Tensor(weight1), from_raw::Tensor(weight2), from_raw::Tensor(weight3), from_raw::Tensor(weight4), from_raw::Tensor(hx_), from_raw::Tensor(cx_tmp), from_raw::Tensor(output), from_raw::Tensor(hy_), from_raw::Tensor(cy_), from_raw::optional::Tensor(grad_output), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::bool_t(reverse), from_raw::int64_t(mode), from_raw::int64_t(hidden_size), from_raw::int64_t(num_layers), from_raw::bool_t(has_biases), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::IntArrayRef(batch_sizes), from_raw::bool_t(batch_first), from_raw::Tensor(workspace))); + LANTERN_FUNCTION_END +} + void* _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_FUNCTION_START @@ -7279,19 +7327,19 @@ void* _lantern__sparse_mm_tensor_tensor(void* sparse, void* dense) LANTERN_FUNCTION_END } -void* _lantern__sparse_sparse_matmul_tensor_tensor(void* self, void* other) +void* _lantern__sparse_mm_tensor_tensor_cstringview(void* sparse, void* dense, void* reduce) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_sparse_sparse_matmul( - from_raw::Tensor(self), from_raw::Tensor(other))); + return make_raw::Tensor(torch::_sparse_mm( + from_raw::Tensor(sparse), from_raw::Tensor(dense), from_raw::string_view(reduce))); LANTERN_FUNCTION_END } -void* _lantern__sparse_mask_helper_tensor_tensor(void* t, void* mask_indices) +void* _lantern__sparse_sparse_matmul_tensor_tensor(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_sparse_mask_helper( - from_raw::Tensor(t), from_raw::Tensor(mask_indices))); + return make_raw::Tensor(torch::_sparse_sparse_matmul( + from_raw::Tensor(self), from_raw::Tensor(other))); LANTERN_FUNCTION_END } @@ -7583,6 +7631,38 @@ void* _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_t LANTERN_FUNCTION_END } +void* _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_native_batch_norm_legit( + from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::Tensor(running_mean), from_raw::Tensor(running_var), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); + LANTERN_FUNCTION_END +} + +void* _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_native_batch_norm_legit_out( + from_raw::Tensor(out), from_raw::Tensor(save_mean), from_raw::Tensor(save_invstd), from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::Tensor(running_mean), from_raw::Tensor(running_var), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); + LANTERN_FUNCTION_END +} + +void* _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* training, void* momentum, void* eps) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_native_batch_norm_legit( + from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); + LANTERN_FUNCTION_END +} + +void* _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_native_batch_norm_legit_out( + from_raw::Tensor(out), from_raw::Tensor(save_mean), from_raw::Tensor(save_invstd), from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); + LANTERN_FUNCTION_END +} + void* _lantern_batch_norm_stats_tensor_double(void* input, void* eps) { LANTERN_FUNCTION_START @@ -8535,6 +8615,14 @@ void* _lantern_Tensor_reshape_tensor_intarrayref(void* self, void* shape) LANTERN_FUNCTION_END } +void* _lantern__reshape_copy_tensor_intarrayref(void* self, void* size) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_reshape_copy( + from_raw::Tensor(self), from_raw::IntArrayRef(size))); + LANTERN_FUNCTION_END +} + void* _lantern__reshape_alias_tensor_intarrayref_intarrayref(void* self, void* size, void* stride) { LANTERN_FUNCTION_START @@ -8727,19 +8815,19 @@ void* _lantern_Tensor_prelu_tensor_tensor(void* self, void* weight) LANTERN_FUNCTION_END } -void* _lantern_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) +void* _lantern__prelu_kernel_tensor_tensor(void* self, void* weight) { LANTERN_FUNCTION_START - return make_raw::tuple(torch::prelu_backward( - from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight))); + return make_raw::Tensor(torch::_prelu_kernel( + from_raw::Tensor(self), from_raw::Tensor(weight))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) +void* _lantern__prelu_kernel_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_FUNCTION_START - return make_raw::tuple(from_raw::Tensor(grad_output).prelu_backward( - from_raw::Tensor(self), from_raw::Tensor(weight))); + return make_raw::tuple(torch::_prelu_kernel_backward( + from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight))); LANTERN_FUNCTION_END } @@ -9687,6 +9775,22 @@ void* _lantern_Tensor_squeeze_tensor_dimname(void* self, void* dim) LANTERN_FUNCTION_END } +void* _lantern_squeeze_tensor_intarrayref(void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::squeeze( + from_raw::Tensor(self), from_raw::IntArrayRef(dim))); + LANTERN_FUNCTION_END +} + +void* _lantern_Tensor_squeeze_tensor_intarrayref(void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(self).squeeze( + from_raw::IntArrayRef(dim))); + LANTERN_FUNCTION_END +} + void* _lantern_Tensor_squeeze__tensor(void* self) { LANTERN_FUNCTION_START @@ -9703,6 +9807,14 @@ void* _lantern_Tensor_squeeze__tensor_intt(void* self, void* dim) LANTERN_FUNCTION_END } +void* _lantern_Tensor_squeeze__tensor_intarrayref(void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(self).squeeze_( + from_raw::IntArrayRef(dim))); + LANTERN_FUNCTION_END +} + void* _lantern_Tensor_squeeze__tensor_dimname(void* self, void* dim) { LANTERN_FUNCTION_START @@ -11119,6 +11231,14 @@ void* _lantern_where_tensor_tensor_scalar(void* condition, void* self, void* oth LANTERN_FUNCTION_END } +void* _lantern_Tensor_where_tensor_tensor_scalar(void* condition, void* self, void* other) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(condition).where( + from_raw::Tensor(self), from_raw::Scalar(other))); + LANTERN_FUNCTION_END +} + void* _lantern_where_tensor_scalar_scalar(void* condition, void* self, void* other) { LANTERN_FUNCTION_START @@ -11559,14 +11679,6 @@ void* _lantern_frexp_out_tensor_tensor_tensor(void* mantissa, void* exponent, vo LANTERN_FUNCTION_END } -void* _lantern_frobenius_norm_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::frobenius_norm( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - void* _lantern_frobenius_norm_tensor_intarrayref_bool(void* self, void* dim, void* keepdim) { LANTERN_FUNCTION_START @@ -11879,6 +11991,22 @@ void* _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(void* sel LANTERN_FUNCTION_END } +void* _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(void* self, void* other, void* reduce) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_sparse_mm_reduce_impl( + from_raw::Tensor(self), from_raw::Tensor(other), from_raw::string_view(reduce))); + LANTERN_FUNCTION_END +} + +void* _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_sparse_mm_reduce_impl_backward( + from_raw::Tensor(self), from_raw::Tensor(grad_out), from_raw::Tensor(weight), from_raw::string_view(reduce), from_raw::Tensor(arg_out), from_raw::vector::bool_t(output_mask))); + LANTERN_FUNCTION_END +} + void* _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_FUNCTION_START @@ -12407,43 +12535,43 @@ void* _lantern_Tensor_to_sparse_tensor_intt(void* self, void* sparse_dim) LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_tensor(void* self) +void* _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(void* self, void* layout, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse( - )); + from_raw::optional::Layout(layout), from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_csr_tensor(void* self) +void* _lantern_Tensor_to_sparse_csr_tensor_intt(void* self, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse_csr( - )); + from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_csc_tensor(void* self) +void* _lantern_Tensor_to_sparse_csc_tensor_intt(void* self, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse_csc( - )); + from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_bsr_tensor_intarrayref(void* self, void* blocksize) +void* _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse_bsr( - from_raw::IntArrayRef(blocksize))); + from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_bsc_tensor_intarrayref(void* self, void* blocksize) +void* _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse_bsc( - from_raw::IntArrayRef(blocksize))); + from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } @@ -12455,11 +12583,11 @@ void* _lantern_Tensor_to_mkldnn_tensor_scalartype(void* self, void* dtype) LANTERN_FUNCTION_END } -void* _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) +void* _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::mkldnn_reorder_conv2d_weight( - from_raw::Tensor(self), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(dilation), from_raw::int64_t(groups))); + from_raw::Tensor(self), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(dilation), from_raw::int64_t(groups), from_raw::IntArrayRef(input_size))); LANTERN_FUNCTION_END } @@ -12959,11 +13087,11 @@ void* _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool LANTERN_FUNCTION_END } -void* _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) +void* _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_FUNCTION_START return make_raw::tuple(torch::lstm_mps_backward( - from_raw::Tensor(grad_y), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::Tensor(z_state), from_raw::Tensor(cell_state_fwd), from_raw::Tensor(input), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first))); + from_raw::Tensor(grad_y), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::Tensor(z_state), from_raw::Tensor(cell_state_fwd), from_raw::Tensor(input), from_raw::Tensor(layersOutputs), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first))); LANTERN_FUNCTION_END } @@ -14567,14 +14695,6 @@ void* _lantern_Tensor_diag_tensor_intt(void* self, void* diagonal) LANTERN_FUNCTION_END } -void* _lantern_diag_backward_tensor_intarrayref_intt(void* grad, void* input_sizes, void* diagonal) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::diag_backward( - from_raw::Tensor(grad), from_raw::IntArrayRef(input_sizes), from_raw::int64_t(diagonal))); - LANTERN_FUNCTION_END -} - void* _lantern_cross_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* dim) { LANTERN_FUNCTION_START @@ -15759,38 +15879,6 @@ void* _lantern_linalg_vander_tensor_intt(void* x, void* N) LANTERN_FUNCTION_END } -void* _lantern_symeig_out_tensor_tensor_tensor_bool_bool(void* e, void* V, void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::symeig_out( - from_raw::Tensor(e), from_raw::Tensor(V), from_raw::Tensor(self), from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - -void* _lantern_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::symeig( - from_raw::Tensor(self), from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - -void* _lantern_Tensor_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(from_raw::Tensor(self).symeig( - from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - -void* _lantern__symeig_helper_tensor_bool_bool(void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_symeig_helper( - from_raw::Tensor(self), from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - void* _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(void* U, void* S, void* V, void* self, void* some, void* compute_uv) { LANTERN_FUNCTION_START @@ -16951,6 +17039,14 @@ void* _lantern_max_out_tensor_tensor_tensor(void* out, void* self, void* other) LANTERN_FUNCTION_END } +void* _lantern_max_out_tensor_tensor(void* out, void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::max_out( + from_raw::Tensor(out), from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + void* _lantern_minimum_tensor_tensor(void* self, void* other) { LANTERN_FUNCTION_START @@ -17703,186 +17799,378 @@ void* _lantern__foreach_div__tensorlist_scalar(void* self, void* scalar) LANTERN_FUNCTION_END } -void* _lantern__foreach_add_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_min_tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_add( - from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha))); + return make_raw::TensorList(torch::_foreach_clamp_min( + from_raw::TensorList(self), from_raw::Scalar(scalar))); LANTERN_FUNCTION_END } -void* _lantern__foreach_add__tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_min__tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_add_(from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + torch::_foreach_clamp_min_(from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_sub_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_max_tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_sub( - from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha))); + return make_raw::TensorList(torch::_foreach_clamp_max( + from_raw::TensorList(self), from_raw::Scalar(scalar))); LANTERN_FUNCTION_END } -void* _lantern__foreach_sub__tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_max__tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_sub_(from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + torch::_foreach_clamp_max_(from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_mul_tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_maximum_tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_mul( - from_raw::TensorList(self), from_raw::TensorList(other))); + return make_raw::TensorList(torch::_foreach_maximum( + from_raw::TensorList(self), from_raw::Scalar(scalar))); LANTERN_FUNCTION_END } -void* _lantern__foreach_mul__tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_maximum__tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_mul_(from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_maximum_(from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_div_tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_minimum_tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_div( - from_raw::TensorList(self), from_raw::TensorList(other))); + return make_raw::TensorList(torch::_foreach_minimum( + from_raw::TensorList(self), from_raw::Scalar(scalar))); LANTERN_FUNCTION_END } -void* _lantern__foreach_div__tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_minimum__tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_div_(from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_minimum_(from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_add_tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_add_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_FUNCTION_START return make_raw::TensorList(torch::_foreach_add( - from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha))); LANTERN_FUNCTION_END } -void* _lantern__foreach_add__tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_add__tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_FUNCTION_START - torch::_foreach_add_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_add_(from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_sub_tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_sub_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_FUNCTION_START return make_raw::TensorList(torch::_foreach_sub( - from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha))); LANTERN_FUNCTION_END } -void* _lantern__foreach_sub__tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_sub__tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_FUNCTION_START - torch::_foreach_sub_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_sub_(from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_div_tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_mul_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_div( - from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + return make_raw::TensorList(torch::_foreach_mul( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_div__tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_mul__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_div_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_mul_(from_raw::TensorList(self), from_raw::TensorList(other)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_mul_tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_div_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_mul( - from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + return make_raw::TensorList(torch::_foreach_div( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_mul__tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_div__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_mul_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_div_(from_raw::TensorList(self), from_raw::TensorList(other)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_exp_tensorlist(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_exp( - from_raw::TensorList(self))); - LANTERN_FUNCTION_END -} - -void* _lantern__foreach_zero__tensorlist(void* self) +void* _lantern__foreach_clamp_min_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_zero_(from_raw::TensorList(self)); - return NULL; + return make_raw::TensorList(torch::_foreach_clamp_min( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_exp__tensorlist(void* self) +void* _lantern__foreach_clamp_min__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_exp_(from_raw::TensorList(self)); + torch::_foreach_clamp_min_(from_raw::TensorList(self), from_raw::TensorList(other)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_sqrt_tensorlist(void* self) +void* _lantern__foreach_clamp_max_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_sqrt( - from_raw::TensorList(self))); + return make_raw::TensorList(torch::_foreach_clamp_max( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_sqrt__tensorlist(void* self) +void* _lantern__foreach_clamp_max__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_sqrt_(from_raw::TensorList(self)); + torch::_foreach_clamp_max_(from_raw::TensorList(self), from_raw::TensorList(other)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_abs_tensorlist(void* self) +void* _lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_abs( - from_raw::TensorList(self))); + return make_raw::TensorList(torch::_foreach_maximum( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_abs__tensorlist(void* self) +void* _lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_abs_(from_raw::TensorList(self)); + torch::_foreach_maximum_(from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_minimum( + from_raw::TensorList(self), from_raw::TensorList(other))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_minimum_(from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_add_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_add( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_add__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_add_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sub_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_sub( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sub__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_sub_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_div_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_div( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_div__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_div_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_mul_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_mul( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_mul__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_mul_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_min_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_clamp_min( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_min__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_min_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_max_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_clamp_max( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_max__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_max_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_maximum_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_maximum( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_maximum__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_maximum_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_minimum( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_minimum_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_exp_tensorlist(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_exp( + from_raw::TensorList(self))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_zero__tensorlist(void* self) +{ + LANTERN_FUNCTION_START + torch::_foreach_zero_(from_raw::TensorList(self)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_exp__tensorlist(void* self) +{ + LANTERN_FUNCTION_START + torch::_foreach_exp_(from_raw::TensorList(self)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sqrt_tensorlist(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_sqrt( + from_raw::TensorList(self))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sqrt__tensorlist(void* self) +{ + LANTERN_FUNCTION_START + torch::_foreach_sqrt_(from_raw::TensorList(self)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_abs_tensorlist(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_abs( + from_raw::TensorList(self))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_abs__tensorlist(void* self) +{ + LANTERN_FUNCTION_START + torch::_foreach_abs_(from_raw::TensorList(self)); return NULL; LANTERN_FUNCTION_END } @@ -18311,6 +18599,14 @@ void* _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar LANTERN_FUNCTION_END } +void* _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_addcdiv_(from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START @@ -18319,6 +18615,14 @@ void* _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar LANTERN_FUNCTION_END } +void* _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_addcmul_(from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_FUNCTION_START @@ -18343,6 +18647,14 @@ void* _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar( LANTERN_FUNCTION_END } +void* _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_addcdiv( + from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars))); + LANTERN_FUNCTION_END +} + void* _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START @@ -18351,43 +18663,51 @@ void* _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar( LANTERN_FUNCTION_END } -void* _lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_maximum( - from_raw::TensorList(self), from_raw::TensorList(other))); + return make_raw::TensorList(torch::_foreach_addcmul( + from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars))); LANTERN_FUNCTION_END } -void* _lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_norm_tensorlist_scalar(void* self, void* ord) { LANTERN_FUNCTION_START - torch::_foreach_maximum_(from_raw::TensorList(self), from_raw::TensorList(other)); - return NULL; + return make_raw::TensorList(torch::_foreach_norm( + from_raw::TensorList(self), from_raw::Scalar(ord))); LANTERN_FUNCTION_END } -void* _lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_minimum( - from_raw::TensorList(self), from_raw::TensorList(other))); + return make_raw::TensorList(torch::_foreach_lerp( + from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::TensorList(weights))); LANTERN_FUNCTION_END } -void* _lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_FUNCTION_START - torch::_foreach_minimum_(from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_lerp_(from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::TensorList(weights)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_norm_tensorlist_scalar(void* self, void* ord) +void* _lantern__foreach_lerp_tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_norm( - from_raw::TensorList(self), from_raw::Scalar(ord))); + return make_raw::TensorList(torch::_foreach_lerp( + from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::Scalar(weight))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_lerp__tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) +{ + LANTERN_FUNCTION_START + torch::_foreach_lerp_(from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::Scalar(weight)); + return NULL; LANTERN_FUNCTION_END } @@ -18423,14 +18743,6 @@ void* _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(void* sor LANTERN_FUNCTION_END } -void* _lantern__torch_cuda_cu_linker_symbol_op_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_torch_cuda_cu_linker_symbol_op( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - void* _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_FUNCTION_START @@ -19791,14 +20103,6 @@ void* _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(void* in LANTERN_FUNCTION_END } -void* _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_linear1d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START @@ -19807,78 +20111,38 @@ void* _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(void* LANTERN_FUNCTION_END } -void* _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bilinear2d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_upsample_bilinear2d_aa( + from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bilinear2d_aa( + return make_raw::Tensor(torch::upsample_trilinear3d( from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bilinear2d_aa_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::upsample_bicubic2d( + from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); LANTERN_FUNCTION_END } -void* _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_trilinear3d( + return make_raw::Tensor(torch::_upsample_bicubic2d_aa( from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); LANTERN_FUNCTION_END } -void* _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_trilinear3d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bicubic2d( - from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bicubic2d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bicubic2d_aa( - from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bicubic2d_aa_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_FUNCTION_START @@ -19895,22 +20159,6 @@ void* _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(void* LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest1d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact1d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_FUNCTION_START @@ -19927,22 +20175,6 @@ void* _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(void* LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest2d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact2d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_FUNCTION_START @@ -19959,22 +20191,6 @@ void* _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(void* LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest3d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact3d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(void* out, void* self, void* output_size, void* align_corners, void* scales) { LANTERN_FUNCTION_START @@ -22911,6 +23127,14 @@ void* _lantern_squeeze_copy_tensor_intt(void* self, void* dim) LANTERN_FUNCTION_END } +void* _lantern_squeeze_copy_tensor_intarrayref(void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::squeeze_copy( + from_raw::Tensor(self), from_raw::IntArrayRef(dim))); + LANTERN_FUNCTION_END +} + void* _lantern_t_copy_tensor(void* self) { LANTERN_FUNCTION_START @@ -23007,6 +23231,30 @@ void* _lantern_unbind_copy_tensor_intt(void* self, void* dim) LANTERN_FUNCTION_END } +void* _lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) +{ + LANTERN_FUNCTION_START + torch::unbind_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::int64_t(dim)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) +{ + LANTERN_FUNCTION_START + torch::split_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::int64_t(split_size), from_raw::int64_t(dim)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) +{ + LANTERN_FUNCTION_START + torch::split_with_sizes_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::IntArrayRef(split_sizes), from_raw::int64_t(dim)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern_view_copy_tensor_intarrayref(void* self, void* size) { LANTERN_FUNCTION_START @@ -23039,463 +23287,263 @@ void* _lantern_alias_copy_tensor(void* self) LANTERN_FUNCTION_END } -void* _lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) +void* _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(void* self, void* padding, void* output_size) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_fw_primal_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(level))); + return make_raw::Tensor(from_raw::Tensor(self).to_padded_tensor( + from_raw::double_t(padding), from_raw::IntArrayRef(output_size))); LANTERN_FUNCTION_END } -void* _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) +void* _lantern__nested_tensor_softmax_with_shape_tensor_tensor(void* self, void* query) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_make_dual_copy_out( - from_raw::Tensor(out), from_raw::Tensor(primal), from_raw::Tensor(tangent), from_raw::int64_t(level))); + return make_raw::Tensor(torch::_nested_tensor_softmax_with_shape( + from_raw::Tensor(self), from_raw::Tensor(query))); LANTERN_FUNCTION_END } -void* _lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::view_as_real_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::_transformer_encoder_layer_fwd( + from_raw::Tensor(src), from_raw::int64_t(embed_dim), from_raw::int64_t(num_heads), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::bool_t(use_gelu), from_raw::bool_t(norm_first), from_raw::double_t(eps), from_raw::Tensor(norm_weight_1), from_raw::Tensor(norm_bias_1), from_raw::Tensor(norm_weight_2), from_raw::Tensor(norm_bias_2), from_raw::Tensor(ffn_weight_1), from_raw::Tensor(ffn_bias_1), from_raw::Tensor(ffn_weight_2), from_raw::Tensor(ffn_bias_2), from_raw::optional::Tensor(mask), from_raw::optional::int64_t(mask_type))); LANTERN_FUNCTION_END } -void* _lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::view_as_complex_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::tuple(torch::_native_multi_head_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask), from_raw::bool_t(need_weights), from_raw::bool_t(average_attn_weights), from_raw::optional::int64_t(mask_type))); LANTERN_FUNCTION_END } -void* _lantern__conj_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_conj_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::scaled_dot_product_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_neg_view_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::tuple(torch::_scaled_dot_product_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(need_attn_weights), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) +void* _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::as_strided_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::IntArrayRef(stride), from_raw::optional::int64_t(storage_offset))); + return make_raw::int64_t(torch::_fused_sdp_choice( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) +void* _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_sparse_broadcast_to_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size))); + return make_raw::tuple(torch::_scaled_dot_product_attention_math( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::optional::Tensor(dropout_mask))); LANTERN_FUNCTION_END } -void* _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) +void* _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::diagonal_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(offset), from_raw::int64_t(dim1), from_raw::int64_t(dim2))); + return make_raw::tuple(torch::_scaled_dot_product_flash_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::bool_t(return_debug_mask))); LANTERN_FUNCTION_END } -void* _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) +void* _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::expand_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::bool_t(implicit))); + return make_raw::tuple(torch::_scaled_dot_product_flash_attention_backward( + from_raw::Tensor(grad_out), from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(out), from_raw::Tensor(logsumexp), from_raw::Tensor(cum_seq_q), from_raw::Tensor(cum_seq_k), from_raw::int64_t(max_q), from_raw::int64_t(max_k), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::int64_t(philox_seed), from_raw::int64_t(philox_offset))); LANTERN_FUNCTION_END } -void* _lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) +void* _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::permute_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(dims))); + return make_raw::tuple(torch::_scaled_dot_product_efficient_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::bool_t(compute_log_sumexp), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) +void* _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_reshape_alias_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::IntArrayRef(stride))); + return make_raw::tuple(torch::_scaled_dot_product_efficient_attention_backward( + from_raw::Tensor(grad_out_), from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(out), from_raw::Tensor(logsumexp), from_raw::bool_t(is_causal), from_raw::bool_t(chunk_grad_outputs))); LANTERN_FUNCTION_END } -void* _lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) +void* _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(void* query, void* key, void* value, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::select_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim), from_raw::int64_t(index))); + return make_raw::bool_t(torch::_chunk_grad_outputs_efficient_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern_detach_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::detach_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::tuple(torch::_flash_attention_forward( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(cum_seq_q), from_raw::Tensor(cum_seq_k), from_raw::int64_t(max_q), from_raw::int64_t(max_k), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::bool_t(return_debug_mask))); LANTERN_FUNCTION_END } -void* _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) +void* _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::slice_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim), from_raw::optional::int64_t(start), from_raw::optional::int64_t(end), from_raw::int64_t(step))); + return make_raw::tuple(torch::_flash_attention_backward( + from_raw::Tensor(grad_out), from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(out), from_raw::Tensor(logsumexp), from_raw::Tensor(cum_seq_q), from_raw::Tensor(cum_seq_k), from_raw::int64_t(max_q), from_raw::int64_t(max_k), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::int64_t(philox_seed), from_raw::int64_t(philox_offset))); LANTERN_FUNCTION_END } -void* _lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) +void* _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal) { LANTERN_FUNCTION_START - torch::split_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::int64_t(split_size), from_raw::int64_t(dim)); - return NULL; + return make_raw::tuple(torch::_efficient_attention_forward( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(cu_seqlens_q), from_raw::optional::Tensor(cu_seqlens_k), from_raw::optional::int64_t(max_seqlen_q), from_raw::bool_t(compute_log_sumexp), from_raw::bool_t(causal))); LANTERN_FUNCTION_END } -void* _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) +void* _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_FUNCTION_START - torch::split_with_sizes_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::IntArrayRef(split_sizes), from_raw::int64_t(dim)); - return NULL; + return make_raw::tuple(torch::_efficient_attention_backward( + from_raw::Tensor(grad_out_), from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(out), from_raw::Tensor(logsumexp), from_raw::bool_t(is_causal), from_raw::bool_t(chunk_grad_outputs))); LANTERN_FUNCTION_END } -void* _lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(void* q, void* k, void* v, void* dropout_p) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::squeeze_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::_triton_scaled_dot_attention( + from_raw::Tensor(q), from_raw::Tensor(k), from_raw::Tensor(v), from_raw::double_t(dropout_p))); LANTERN_FUNCTION_END } -void* _lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) +void* _lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::squeeze_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim))); + return make_raw::Tensor(torch::_triton_multi_head_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask))); LANTERN_FUNCTION_END } -void* _lantern_t_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_airy_ai_tensor(void* x) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::t_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::special_airy_ai( + from_raw::Tensor(x))); LANTERN_FUNCTION_END } -void* _lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) +void* _lantern_special_airy_ai_out_tensor_tensor(void* out, void* x) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::transpose_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim0), from_raw::int64_t(dim1))); + return make_raw::Tensor(torch::special_airy_ai_out( + from_raw::Tensor(out), from_raw::Tensor(x))); LANTERN_FUNCTION_END } -void* _lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) +void* _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::unsqueeze_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim))); + return make_raw::tuple(torch::_transformer_decoder_only_layer_fwd( + from_raw::Tensor(src), from_raw::int64_t(embed_dim), from_raw::int64_t(num_heads), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::bool_t(use_gelu), from_raw::bool_t(norm_first), from_raw::double_t(eps), from_raw::Tensor(norm_weight_1), from_raw::Tensor(norm_bias_1), from_raw::Tensor(norm_weight_2), from_raw::Tensor(norm_bias_2), from_raw::Tensor(ffn_weight_1), from_raw::Tensor(ffn_bias_1), from_raw::Tensor(ffn_weight_2), from_raw::Tensor(ffn_bias_2), from_raw::optional::Tensor(mask), from_raw::optional::Tensor(incr_key), from_raw::optional::Tensor(incr_value))); LANTERN_FUNCTION_END } -void* _lantern__indices_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* incr_key, void* incr_value, void* need_weights, void* average_attn_weights) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_indices_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::tuple(torch::_native_decoder_only_multi_head_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask), from_raw::optional::Tensor(incr_key), from_raw::optional::Tensor(incr_value), from_raw::bool_t(need_weights), from_raw::bool_t(average_attn_weights))); LANTERN_FUNCTION_END } -void* _lantern__values_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_j0_tensor(void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_values_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::special_bessel_j0( + from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_indices_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_j0_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::indices_copy_out( + return make_raw::Tensor(torch::special_bessel_j0_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_values_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_j1_tensor(void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::values_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::special_bessel_j1( + from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_j1_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::crow_indices_copy_out( + return make_raw::Tensor(torch::special_bessel_j1_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_y0_tensor(void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::col_indices_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::special_bessel_y0( + from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) +void* _lantern_special_bessel_y0_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - torch::unbind_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::int64_t(dim)); - return NULL; + return make_raw::Tensor(torch::special_bessel_y0_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) +void* _lantern_special_bessel_y1_tensor(void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::view_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size))); + return make_raw::Tensor(torch::special_bessel_y1( + from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) +void* _lantern_special_bessel_y1_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::view_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::ScalarType(dtype))); + return make_raw::Tensor(torch::special_bessel_y1_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) +void* _lantern_special_chebyshev_polynomial_t_tensor_tensor(void* x, void* n) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::unfold_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dimension), from_raw::int64_t(size), from_raw::int64_t(step))); + return make_raw::Tensor(torch::special_chebyshev_polynomial_t( + from_raw::Tensor(x), from_raw::Tensor(n))); LANTERN_FUNCTION_END } -void* _lantern_alias_copy_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::alias_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(void* self, void* padding, void* output_size) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(from_raw::Tensor(self).to_padded_tensor( - from_raw::double_t(padding), from_raw::IntArrayRef(output_size))); - LANTERN_FUNCTION_END -} - -void* _lantern__nested_tensor_softmax_with_shape_tensor_tensor(void* self, void* query) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_nested_tensor_softmax_with_shape( - from_raw::Tensor(self), from_raw::Tensor(query))); - LANTERN_FUNCTION_END -} - -void* _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(void* self, void* weight, void* bias, void* eps) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(from_raw::Tensor(self)._nested_tensor_layer_norm( - from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::double_t(eps))); - LANTERN_FUNCTION_END -} - -void* _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_transformer_encoder_layer_fwd( - from_raw::Tensor(src), from_raw::int64_t(embed_dim), from_raw::int64_t(num_heads), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::bool_t(use_gelu), from_raw::bool_t(norm_first), from_raw::double_t(eps), from_raw::Tensor(norm_weight_1), from_raw::Tensor(norm_bias_1), from_raw::Tensor(norm_weight_2), from_raw::Tensor(norm_bias_2), from_raw::Tensor(ffn_weight_1), from_raw::Tensor(ffn_bias_1), from_raw::Tensor(ffn_weight_2), from_raw::Tensor(ffn_bias_2), from_raw::optional::Tensor(mask), from_raw::optional::int64_t(mask_type))); - LANTERN_FUNCTION_END -} - -void* _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_native_multi_head_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask), from_raw::bool_t(need_weights), from_raw::bool_t(average_attn_weights), from_raw::optional::int64_t(mask_type))); - LANTERN_FUNCTION_END -} - -void* _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_scaled_dot_product_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(need_attn_weights), from_raw::bool_t(is_causal))); - LANTERN_FUNCTION_END -} - -void* _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_scaled_dot_product_attention_forward( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(need_attn_weights), from_raw::bool_t(is_causal))); - LANTERN_FUNCTION_END -} - -void* _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_scaled_dot_product_attention_math( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(need_attn_weights), from_raw::bool_t(is_causal))); - LANTERN_FUNCTION_END -} - -void* _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(void* q, void* k, void* v, void* dropout_p) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_triton_scaled_dot_attention( - from_raw::Tensor(q), from_raw::Tensor(k), from_raw::Tensor(v), from_raw::double_t(dropout_p))); - LANTERN_FUNCTION_END -} - -void* _lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_triton_multi_head_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_airy_ai_tensor(void* x) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_airy_ai( - from_raw::Tensor(x))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_airy_ai_out_tensor_tensor(void* out, void* x) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_airy_ai_out( - from_raw::Tensor(out), from_raw::Tensor(x))); - LANTERN_FUNCTION_END -} - -void* _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_flash_scaled_dot_product_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(cum_seq_q), from_raw::Tensor(cum_seq_k), from_raw::int64_t(max_q), from_raw::int64_t(max_k), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal))); - LANTERN_FUNCTION_END -} - -void* _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_transformer_decoder_only_layer_fwd( - from_raw::Tensor(src), from_raw::int64_t(embed_dim), from_raw::int64_t(num_heads), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::bool_t(use_gelu), from_raw::bool_t(norm_first), from_raw::double_t(eps), from_raw::Tensor(norm_weight_1), from_raw::Tensor(norm_bias_1), from_raw::Tensor(norm_weight_2), from_raw::Tensor(norm_bias_2), from_raw::Tensor(ffn_weight_1), from_raw::Tensor(ffn_bias_1), from_raw::Tensor(ffn_weight_2), from_raw::Tensor(ffn_bias_2), from_raw::optional::Tensor(mask), from_raw::optional::Tensor(incr_key), from_raw::optional::Tensor(incr_value))); - LANTERN_FUNCTION_END -} - -void* _lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* incr_key, void* incr_value, void* need_weights, void* average_attn_weights) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_native_decoder_only_multi_head_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask), from_raw::optional::Tensor(incr_key), from_raw::optional::Tensor(incr_value), from_raw::bool_t(need_weights), from_raw::bool_t(average_attn_weights))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_j0_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_j0( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_j0_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_j0_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_j1_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_j1( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_j1_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_j1_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_y0_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_y0( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_y0_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_y0_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_y1_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_y1( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_y1_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_y1_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_chebyshev_polynomial_t_tensor_tensor(void* x, void* n) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_chebyshev_polynomial_t( - from_raw::Tensor(x), from_raw::Tensor(n))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_chebyshev_polynomial_t_scalar_tensor(void* x, void* n) +void* _lantern_special_chebyshev_polynomial_t_scalar_tensor(void* x, void* n) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::special_chebyshev_polynomial_t( @@ -24191,6 +24239,14 @@ void* _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorli LANTERN_FUNCTION_END } +void* _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) +{ + LANTERN_FUNCTION_START + torch::_fused_adamw_(from_raw::TensorList(self), from_raw::TensorList(grads), from_raw::TensorList(exp_avgs), from_raw::TensorList(exp_avg_sqs), from_raw::TensorList(max_exp_avg_sqs), from_raw::TensorList(state_steps), from_raw::double_t(lr), from_raw::double_t(beta1), from_raw::double_t(beta2), from_raw::double_t(weight_decay), from_raw::double_t(eps), from_raw::bool_t(amsgrad), from_raw::bool_t(maximize), from_raw::optional::Tensor(grad_scale), from_raw::optional::Tensor(found_inf)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* self_num_batch_dims) { LANTERN_FUNCTION_START @@ -24591,6 +24647,14 @@ void* _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref LANTERN_FUNCTION_END } +void* _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_ctc_loss_out( + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(log_probs), from_raw::Tensor(targets), from_raw::Tensor(input_lengths), from_raw::Tensor(target_lengths), from_raw::int64_t(blank), from_raw::bool_t(zero_infinity))); + LANTERN_FUNCTION_END +} + void* _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity) { LANTERN_FUNCTION_START @@ -25095,18 +25159,10 @@ void* _lantern__aminmax_out_tensor_tensor_tensor_intt_bool(void* out0, void* out LANTERN_FUNCTION_END } -void* _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_mps_max_pool2d_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation), from_raw::bool_t(ceil_mode))); - LANTERN_FUNCTION_END -} - -void* _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) +void* _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::mps_max_pool2d_backward_out( + return make_raw::Tensor(torch::max_pool2d_backward_out( from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation), from_raw::bool_t(ceil_mode))); LANTERN_FUNCTION_END } @@ -25199,6 +25255,22 @@ void* _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_in LANTERN_FUNCTION_END } +void* _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::mkldnn_rnn_layer_out( + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(out3), from_raw::Tensor(input), from_raw::Tensor(weight0), from_raw::Tensor(weight1), from_raw::Tensor(weight2), from_raw::Tensor(weight3), from_raw::Tensor(hx_), from_raw::Tensor(cx_), from_raw::bool_t(reverse), from_raw::IntArrayRef(batch_sizes), from_raw::int64_t(mode), from_raw::int64_t(hidden_size), from_raw::int64_t(num_layers), from_raw::bool_t(has_biases), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first), from_raw::bool_t(train))); + LANTERN_FUNCTION_END +} + +void* _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::mkldnn_rnn_layer_backward_out( + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(out3), from_raw::Tensor(out4), from_raw::Tensor(out5), from_raw::Tensor(out6), from_raw::Tensor(input), from_raw::Tensor(weight1), from_raw::Tensor(weight2), from_raw::Tensor(weight3), from_raw::Tensor(weight4), from_raw::Tensor(hx_), from_raw::Tensor(cx_tmp), from_raw::Tensor(output), from_raw::Tensor(hy_), from_raw::Tensor(cy_), from_raw::optional::Tensor(grad_output), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::bool_t(reverse), from_raw::int64_t(mode), from_raw::int64_t(hidden_size), from_raw::int64_t(num_layers), from_raw::bool_t(has_biases), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::IntArrayRef(batch_sizes), from_raw::bool_t(batch_first), from_raw::Tensor(workspace))); + LANTERN_FUNCTION_END +} + void* _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_FUNCTION_START @@ -25263,19 +25335,19 @@ void* _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(void* out, void* s LANTERN_FUNCTION_END } -void* _lantern__sparse_mask_helper_out_tensor_tensor_tensor(void* out, void* t, void* mask_indices) +void* _lantern_mul_out_tensor_tensor_scalar(void* out, void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_sparse_mask_helper_out( - from_raw::Tensor(out), from_raw::Tensor(t), from_raw::Tensor(mask_indices))); + return make_raw::Tensor(torch::mul_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Scalar(other))); LANTERN_FUNCTION_END } -void* _lantern_mul_out_tensor_tensor_scalar(void* out, void* self, void* other) +void* _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::mul_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Scalar(other))); + return make_raw::tuple(torch::_native_batch_norm_legit_functional( + from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::Tensor(running_mean), from_raw::Tensor(running_var), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); LANTERN_FUNCTION_END } @@ -25535,22 +25607,6 @@ void* _lantern_relu_out_tensor_tensor(void* out, void* self) LANTERN_FUNCTION_END } -void* _lantern_prelu_out_tensor_tensor_tensor(void* out, void* self, void* weight) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::prelu_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight))); - LANTERN_FUNCTION_END -} - -void* _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* grad_output, void* self, void* weight) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::prelu_backward_out( - from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight))); - LANTERN_FUNCTION_END -} - void* _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(void* out, void* grad_output, void* input_sizes, void* dim, void* index) { LANTERN_FUNCTION_START @@ -26199,43 +26255,43 @@ void* _lantern_to_sparse_out_tensor_tensor_intt(void* out, void* self, void* spa LANTERN_FUNCTION_END } -void* _lantern_to_sparse_out_tensor_tensor(void* out, void* self) +void* _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(void* out, void* self, void* layout, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::optional::Layout(layout), from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_to_sparse_csr_out_tensor_tensor(void* out, void* self) +void* _lantern_to_sparse_csr_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_csr_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_to_sparse_csc_out_tensor_tensor(void* out, void* self) +void* _lantern_to_sparse_csc_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_csc_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) +void* _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_bsr_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(blocksize))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) +void* _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_bsc_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(blocksize))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } @@ -26247,11 +26303,11 @@ void* _lantern_to_mkldnn_out_tensor_tensor_scalartype(void* out, void* self, voi LANTERN_FUNCTION_END } -void* _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) +void* _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::mkldnn_reorder_conv2d_weight_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(dilation), from_raw::int64_t(groups))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(dilation), from_raw::int64_t(groups), from_raw::IntArrayRef(input_size))); LANTERN_FUNCTION_END } @@ -26423,18 +26479,18 @@ void* _lantern__to_copy_out_tensor_tensor_bool_memoryformat(void* out, void* sel LANTERN_FUNCTION_END } -void* _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) +void* _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_FUNCTION_START return make_raw::tuple(torch::_lstm_mps_out( - from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(out3), from_raw::Tensor(out4), from_raw::Tensor(input), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first))); + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(out3), from_raw::Tensor(out4), from_raw::Tensor(out5), from_raw::Tensor(input), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first))); LANTERN_FUNCTION_END } -void* _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) +void* _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_FUNCTION_START - torch::lstm_mps_backward_out(from_raw::Tensor(out0), from_raw::TensorList(out1), from_raw::TensorList(out2), from_raw::Tensor(grad_y), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::Tensor(z_state), from_raw::Tensor(cell_state_fwd), from_raw::Tensor(input), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first)); + torch::lstm_mps_backward_out(from_raw::Tensor(out0), from_raw::TensorList(out1), from_raw::TensorList(out2), from_raw::Tensor(grad_y), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::Tensor(z_state), from_raw::Tensor(cell_state_fwd), from_raw::Tensor(input), from_raw::Tensor(layersOutputs), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first)); return NULL; LANTERN_FUNCTION_END } @@ -26847,14 +26903,6 @@ void* _lantern_trace_out_tensor_tensor(void* out, void* self) LANTERN_FUNCTION_END } -void* _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(void* out0, void* out1, void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_symeig_helper_out( - from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(self), from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - void* _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(void* out, void* self, void* A, void* upper) { LANTERN_FUNCTION_START @@ -26991,42 +27039,106 @@ void* _lantern__foreach_div_out_tensorlist_tensorlist_scalar(void* out, void* se LANTERN_FUNCTION_END } -void* _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_add_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + torch::_foreach_clamp_min_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_sub_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + torch::_foreach_clamp_max_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +void* _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_mul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_maximum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +void* _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_div_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_minimum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +void* _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) { LANTERN_FUNCTION_START - torch::_foreach_add_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_add_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) +{ + LANTERN_FUNCTION_START + torch::_foreach_sub_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_mul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_div_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_min_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_max_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_maximum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_minimum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_add_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); return NULL; LANTERN_FUNCTION_END } @@ -27055,6 +27167,38 @@ void* _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(void* out, LANTERN_FUNCTION_END } +void* _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_min_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_max_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_maximum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_minimum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern__foreach_exp_out_tensorlist_tensorlist(void* out, void* self) { LANTERN_FUNCTION_START @@ -27319,26 +27463,26 @@ void* _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_ LANTERN_FUNCTION_END } -void* _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) +void* _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START - torch::_foreach_addcmul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::vector::Scalar(scalars)); + torch::_foreach_addcdiv_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +void* _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START - torch::_foreach_maximum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_addcmul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::vector::Scalar(scalars)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +void* _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START - torch::_foreach_minimum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_addcmul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars)); return NULL; LANTERN_FUNCTION_END } @@ -27351,19 +27495,27 @@ void* _lantern__foreach_norm_out_tensorlist_tensorlist_scalar(void* out, void* s LANTERN_FUNCTION_END } -void* _lantern_bucketize_out_tensor_scalar_tensor_bool_bool(void* out, void* self, void* boundaries, void* out_int32, void* right) +void* _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(void* out, void* self, void* tensors1, void* weights) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::bucketize_out( - from_raw::Tensor(out), from_raw::Scalar(self), from_raw::Tensor(boundaries), from_raw::bool_t(out_int32), from_raw::bool_t(right))); + torch::_foreach_lerp_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::TensorList(weights)); + return NULL; LANTERN_FUNCTION_END } -void* _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(void* out, void* self) +void* _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensors1, void* weight) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_torch_cuda_cu_linker_symbol_op_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + torch::_foreach_lerp_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::Scalar(weight)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern_bucketize_out_tensor_scalar_tensor_bool_bool(void* out, void* self, void* boundaries, void* out_int32, void* right) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::bucketize_out( + from_raw::Tensor(out), from_raw::Scalar(self), from_raw::Tensor(boundaries), from_raw::bool_t(out_int32), from_raw::bool_t(right))); LANTERN_FUNCTION_END } @@ -27447,315 +27599,339 @@ void* _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(void* out, LANTERN_FUNCTION_END } -void* _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_linear1d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::tuple(torch::_slow_conv2d_backward_out( + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::vector::bool_t(output_mask))); LANTERN_FUNCTION_END } -void* _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_linear1d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::conv_depthwise3d_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); LANTERN_FUNCTION_END } -void* _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bilinear2d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::slow_conv_dilated2d_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); LANTERN_FUNCTION_END } -void* _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern_slow_conv_dilated3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bilinear2d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::slow_conv_dilated3d_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern_isinf_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bilinear2d_aa_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::isinf_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern_linalg_matrix_exp_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bilinear2d_aa_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::linalg_matrix_exp_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__test_optional_intlist_out_tensor_tensor_intarrayref(void* out, void* values, void* addends) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_trilinear3d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_optional_intlist_out( + from_raw::Tensor(out), from_raw::Tensor(values), from_raw::IntArrayRef(addends))); LANTERN_FUNCTION_END } -void* _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern__test_optional_filled_intlist_out_tensor_tensor_intarrayref(void* out, void* values, void* addends) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_trilinear3d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_optional_filled_intlist_out( + from_raw::Tensor(out), from_raw::Tensor(values), from_raw::IntArrayRef(addends))); LANTERN_FUNCTION_END } -void* _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__test_optional_floatlist_out_tensor_tensor_arrayrefdouble(void* out, void* values, void* addends) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bicubic2d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_optional_floatlist_out( + from_raw::Tensor(out), from_raw::Tensor(values), from_raw::optional::DoubleArrayRef(addends))); LANTERN_FUNCTION_END } -void* _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern__test_warn_in_autograd_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bicubic2d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_warn_in_autograd_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__test_autograd_multiple_dispatch_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bicubic2d_aa_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_autograd_multiple_dispatch_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern__test_autograd_multiple_dispatch_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bicubic2d_aa_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_autograd_multiple_dispatch_view_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar(void* out, void* data, void* reduce, void* lengths, void* indices, void* offsets, void* axis, void* unsafe, void* initial) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest1d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::segment_reduce_out( + from_raw::Tensor(out), from_raw::Tensor(data), from_raw::string_view(reduce), from_raw::optional::Tensor(lengths), from_raw::optional::Tensor(indices), from_raw::optional::Tensor(offsets), from_raw::int64_t(axis), from_raw::bool_t(unsafe), from_raw::optional::Scalar(initial))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(void* out, void* grad, void* output, void* data, void* reduce, void* lengths, void* offsets, void* axis, void* initial) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact1d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_segment_reduce_backward_out( + from_raw::Tensor(out), from_raw::Tensor(grad), from_raw::Tensor(output), from_raw::Tensor(data), from_raw::string_view(reduce), from_raw::optional::Tensor(lengths), from_raw::optional::Tensor(offsets), from_raw::int64_t(axis), from_raw::optional::Scalar(initial))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest1d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_nested_tensor_from_tensor_list_out( + from_raw::Tensor(out), from_raw::TensorList(list), from_raw::optional::ScalarType(dtype), from_raw::optional::Layout(layout), from_raw::optional::Device(device), from_raw::optional::bool_t(pin_memory))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact1d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_fw_primal_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(level))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest2d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_make_dual_copy_out( + from_raw::Tensor(out), from_raw::Tensor(primal), from_raw::Tensor(tangent), from_raw::int64_t(level))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact2d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::view_as_real_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest2d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::view_as_complex_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact2d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_conj_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest3d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_neg_view_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact3d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::as_strided_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::IntArrayRef(stride), from_raw::optional::int64_t(storage_offset))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest3d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_sparse_broadcast_to_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact3d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::diagonal_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(offset), from_raw::int64_t(dim1), from_raw::int64_t(dim2))); LANTERN_FUNCTION_END } -void* _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask) +void* _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_FUNCTION_START - return make_raw::tuple(torch::_slow_conv2d_backward_out( - from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::vector::bool_t(output_mask))); + return make_raw::Tensor(torch::expand_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::bool_t(implicit))); LANTERN_FUNCTION_END } -void* _lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) +void* _lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::conv_depthwise3d_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); + return make_raw::Tensor(torch::permute_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(dims))); LANTERN_FUNCTION_END } -void* _lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) +void* _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::slow_conv_dilated2d_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); + return make_raw::Tensor(torch::_reshape_alias_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::IntArrayRef(stride))); LANTERN_FUNCTION_END } -void* _lantern_slow_conv_dilated3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) +void* _lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::slow_conv_dilated3d_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); + return make_raw::Tensor(torch::select_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim), from_raw::int64_t(index))); LANTERN_FUNCTION_END } -void* _lantern_isinf_out_tensor_tensor(void* out, void* self) +void* _lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::isinf_out( + return make_raw::Tensor(torch::detach_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_linalg_matrix_exp_out_tensor_tensor(void* out, void* self) +void* _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::linalg_matrix_exp_out( + return make_raw::Tensor(torch::slice_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim), from_raw::optional::int64_t(start), from_raw::optional::int64_t(end), from_raw::int64_t(step))); + LANTERN_FUNCTION_END +} + +void* _lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::squeeze_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__test_optional_intlist_out_tensor_tensor_intarrayref(void* out, void* values, void* addends) +void* _lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_optional_intlist_out( - from_raw::Tensor(out), from_raw::Tensor(values), from_raw::IntArrayRef(addends))); + return make_raw::Tensor(torch::squeeze_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim))); LANTERN_FUNCTION_END } -void* _lantern__test_optional_filled_intlist_out_tensor_tensor_intarrayref(void* out, void* values, void* addends) +void* _lantern_squeeze_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dim) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_optional_filled_intlist_out( - from_raw::Tensor(out), from_raw::Tensor(values), from_raw::IntArrayRef(addends))); + return make_raw::Tensor(torch::squeeze_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(dim))); LANTERN_FUNCTION_END } -void* _lantern__test_optional_floatlist_out_tensor_tensor_arrayrefdouble(void* out, void* values, void* addends) +void* _lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_optional_floatlist_out( - from_raw::Tensor(out), from_raw::Tensor(values), from_raw::optional::DoubleArrayRef(addends))); + return make_raw::Tensor(torch::t_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__test_warn_in_autograd_out_tensor_tensor(void* out, void* self) +void* _lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_warn_in_autograd_out( + return make_raw::Tensor(torch::transpose_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim0), from_raw::int64_t(dim1))); + LANTERN_FUNCTION_END +} + +void* _lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::unsqueeze_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim))); + LANTERN_FUNCTION_END +} + +void* _lantern__indices_copy_out_tensor_tensor(void* out, void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_indices_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__test_autograd_multiple_dispatch_out_tensor_tensor(void* out, void* self) +void* _lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_autograd_multiple_dispatch_out( + return make_raw::Tensor(torch::_values_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__test_autograd_multiple_dispatch_view_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_autograd_multiple_dispatch_view_copy_out( + return make_raw::Tensor(torch::indices_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar(void* out, void* data, void* reduce, void* lengths, void* indices, void* offsets, void* axis, void* unsafe, void* initial) +void* _lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::segment_reduce_out( - from_raw::Tensor(out), from_raw::Tensor(data), from_raw::string_view(reduce), from_raw::optional::Tensor(lengths), from_raw::optional::Tensor(indices), from_raw::optional::Tensor(offsets), from_raw::int64_t(axis), from_raw::bool_t(unsafe), from_raw::optional::Scalar(initial))); + return make_raw::Tensor(torch::values_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(void* out, void* grad, void* output, void* data, void* reduce, void* lengths, void* offsets, void* axis, void* initial) +void* _lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_segment_reduce_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad), from_raw::Tensor(output), from_raw::Tensor(data), from_raw::string_view(reduce), from_raw::optional::Tensor(lengths), from_raw::optional::Tensor(offsets), from_raw::int64_t(axis), from_raw::optional::Scalar(initial))); + return make_raw::Tensor(torch::crow_indices_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory) +void* _lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_nested_tensor_from_tensor_list_out( - from_raw::Tensor(out), from_raw::TensorList(list), from_raw::optional::ScalarType(dtype), from_raw::optional::Layout(layout), from_raw::optional::Device(device), from_raw::optional::bool_t(pin_memory))); + return make_raw::Tensor(torch::col_indices_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } @@ -27775,19 +27951,43 @@ void* _lantern_row_indices_copy_out_tensor_tensor(void* out, void* self) LANTERN_FUNCTION_END } -void* _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(void* out, void* self, void* padding, void* output_size) +void* _lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::to_padded_tensor_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::double_t(padding), from_raw::IntArrayRef(output_size))); + return make_raw::Tensor(torch::view_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size))); + LANTERN_FUNCTION_END +} + +void* _lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::view_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::ScalarType(dtype))); LANTERN_FUNCTION_END } -void* _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(void* out, void* self, void* weight, void* bias, void* eps) +void* _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_nested_tensor_layer_norm_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::double_t(eps))); + return make_raw::Tensor(torch::unfold_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dimension), from_raw::int64_t(size), from_raw::int64_t(step))); + LANTERN_FUNCTION_END +} + +void* _lantern_alias_copy_out_tensor_tensor(void* out, void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::alias_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + +void* _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(void* out, void* self, void* padding, void* output_size) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::to_padded_tensor_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::double_t(padding), from_raw::IntArrayRef(output_size))); LANTERN_FUNCTION_END } @@ -27863,4 +28063,20 @@ void* _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlis LANTERN_FUNCTION_END } +void* _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) +{ + LANTERN_FUNCTION_START + torch::_fused_adamw_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(grads), from_raw::TensorList(exp_avgs), from_raw::TensorList(exp_avg_sqs), from_raw::TensorList(max_exp_avg_sqs), from_raw::TensorList(state_steps), from_raw::double_t(lr), from_raw::double_t(beta1), from_raw::double_t(beta2), from_raw::double_t(weight_decay), from_raw::double_t(eps), from_raw::bool_t(amsgrad), from_raw::bool_t(maximize), from_raw::optional::Tensor(grad_scale), from_raw::optional::Tensor(found_inf)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_fused_adamw( + from_raw::TensorList(self), from_raw::TensorList(grads), from_raw::TensorList(exp_avgs), from_raw::TensorList(exp_avg_sqs), from_raw::TensorList(max_exp_avg_sqs), from_raw::TensorList(state_steps), from_raw::double_t(lr), from_raw::double_t(beta1), from_raw::double_t(beta2), from_raw::double_t(weight_decay), from_raw::double_t(eps), from_raw::bool_t(amsgrad), from_raw::bool_t(maximize), from_raw::optional::Tensor(grad_scale), from_raw::optional::Tensor(found_inf))); + LANTERN_FUNCTION_END +} + /* Autogen Body -- End */ diff --git a/tools/torchgen/R/cpp.R b/tools/torchgen/R/cpp.R index 1b29cb9cb8..ebbf67bec3 100644 --- a/tools/torchgen/R/cpp.R +++ b/tools/torchgen/R/cpp.R @@ -679,7 +679,9 @@ cpp <- function(path) { purrr::discard(~.x$name == "range" && length(.x$arguments) == 3) %>% purrr::discard(~.x$name == "range_out" && length(.x$arguments) == 3) %>% purrr::discard(~.x$name == "arange" && length(.x$arguments) == 3) %>% - purrr::discard(~.x$name == "stft" && length(.x$arguments) == 8) + purrr::discard(~.x$name == "stft" && length(.x$arguments) == 8) %>% + purrr::discard(~str_detect(.x$name, "var") && "correction" %in% map_chr(.x$arguments, ~.x$name)) %>% + purrr::discard(~str_detect(.x$name, "std") && "correction" %in% map_chr(.x$arguments, ~.x$name)) pb <- NULL diff --git a/tools/torchgen/R/utils.R b/tools/torchgen/R/utils.R index fa01dabb47..86db662448 100644 --- a/tools/torchgen/R/utils.R +++ b/tools/torchgen/R/utils.R @@ -7,7 +7,7 @@ #' @export declarations <- function() { - version <- getOption("torchgen.version", default = "1.13.1") + version <- getOption("torchgen.version", default = "2.0.1") path <- getOption("torchgen.path") if (is.null(path)) { diff --git a/tools/torchgen/inst/declaration/Declarations-1.13.1.yaml b/tools/torchgen/inst/declaration/Declarations-2.0.1.yaml similarity index 97% rename from tools/torchgen/inst/declaration/Declarations-1.13.1.yaml rename to tools/torchgen/inst/declaration/Declarations-2.0.1.yaml index 30d70db719..88688e1499 100644 --- a/tools/torchgen/inst/declaration/Declarations-1.13.1.yaml +++ b/tools/torchgen/inst/declaration/Declarations-2.0.1.yaml @@ -6150,6 +6150,113 @@ with_gil: false deprecated: false has_math_kernel: true +- name: _is_all_true + operator_name: _is_all_true + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_is_all_true(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _is_any_true + operator_name: _is_any_true + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_is_any_true(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_check_tensor + operator_name: _test_check_tensor + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_check_tensor(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true - name: all operator_name: all overload_name: dim @@ -10177,11 +10284,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: bilinear operator_name: bilinear overload_name: '' @@ -11999,7 +12106,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::broadcast_to(Tensor(a) self, int[] size) -> Tensor(a) + schema_string: aten::broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -13072,7 +13179,7 @@ type: ::std::vector inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: false with_gil: false deprecated: false @@ -13082,7 +13189,7 @@ overload_name: sections manual_kernel_registration: false category_override: '' - schema_string: aten::tensor_split.sections(Tensor(a -> *) self, int sections, int dim=0) -> Tensor(a)[] + schema_string: aten::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -13140,7 +13247,7 @@ overload_name: indices manual_kernel_registration: false category_override: '' - schema_string: aten::tensor_split.indices(Tensor(a -> *) self, int[] indices, int dim=0) -> Tensor(a)[] + schema_string: aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -14875,7 +14982,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::constant_pad_nd(Tensor self, int[] pad, Scalar value=0) -> Tensor + schema_string: aten::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -14981,7 +15088,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor + schema_string: aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -15096,7 +15203,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) + schema_string: aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -15486,7 +15593,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor + schema_string: aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -15881,7 +15988,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) + schema_string: aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -17272,11 +17379,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: copy_ operator_name: copy_ overload_name: '' @@ -24191,7 +24298,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor + schema_string: aten::embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -24272,7 +24379,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor + schema_string: aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -24357,7 +24464,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor + schema_string: aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25234,7 +25341,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25381,7 +25488,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25508,7 +25615,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -31728,7 +31835,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_fft_c2c(Tensor self, int[] dim, int normalization, bool forward) -> Tensor + schema_string: aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -31793,7 +31900,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_fft_c2c.out(Tensor self, int[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -34412,7 +34519,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::layer_norm(Tensor input, int[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor + schema_string: aten::layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -39598,7 +39705,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, int[] sizes, bool keepdim) -> Tensor + schema_string: aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, SymInt[] sizes, bool keepdim) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40106,17 +40213,128 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: true -- name: _mps_max_pool2d - operator_name: _mps_max_pool2d +- name: max_pool2d_backward + operator_name: max_pool2d_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: ceil_mode + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: ceil_mode + type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_max_pool2d + operator_name: mkldnn_max_pool2d overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_mps_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40212,12 +40430,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mps_max_pool2d_backward - operator_name: mps_max_pool2d_backward +- name: mkldnn_max_pool2d_backward + operator_name: mkldnn_max_pool2d_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mps_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40227,7 +40445,12 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef @@ -40262,7 +40485,7 @@ is_nullable: false name: ceil_mode type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -40272,7 +40495,12 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef @@ -40323,12 +40551,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mkldnn_max_pool2d - operator_name: mkldnn_max_pool2d +- name: mkldnn_max_pool3d + operator_name: mkldnn_max_pool3d overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40339,28 +40567,28 @@ dynamic_type: at::IntArrayRef is_nullable: false name: kernel_size - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: '{}' dynamic_type: at::IntArrayRef is_nullable: false name: stride - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 0 dynamic_type: at::IntArrayRef is_nullable: false name: padding - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 1 dynamic_type: at::IntArrayRef is_nullable: false name: dilation - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: false @@ -40379,250 +40607,28 @@ dynamic_type: at::IntArrayRef is_nullable: false name: kernel_size - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: '{}' dynamic_type: at::IntArrayRef is_nullable: false name: stride - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 0 dynamic_type: at::IntArrayRef is_nullable: false name: padding - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 1 dynamic_type: at::IntArrayRef is_nullable: false name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_max_pool2d_backward - operator_name: mkldnn_max_pool2d_backward - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_max_pool3d - operator_name: mkldnn_max_pool3d - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 + size: 3 type: at::IntArrayRef - annotation: null default: false @@ -42969,7 +42975,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups) -> Tensor + schema_string: aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43059,12 +43065,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: miopen_batch_norm - operator_name: miopen_batch_norm +- name: mkldnn_rnn_layer + operator_name: mkldnn_rnn_layer overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) + schema_string: aten::mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -43074,39 +43080,506 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: weight + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + name: result3 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_backward + operator_name: mkldnn_rnn_layer_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer_backward(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: bias + name: grad_output type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: running_mean + name: grad_hy type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: running_var + name: grad_cy type: const c10::optional & - annotation: null dynamic_type: bool is_nullable: false - name: training + name: reverse type: bool - annotation: null - dynamic_type: double + dynamic_type: int64_t is_nullable: false - name: exponential_average_factor - type: double + name: mode + type: int64_t - annotation: null - dynamic_type: double + dynamic_type: int64_t is_nullable: false - name: epsilon - type: double - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double) + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + name: result3 + type: at::Tensor + - dynamic_type: at::Tensor + name: result4 + type: at::Tensor + - dynamic_type: at::Tensor + name: result5 + type: at::Tensor + - dynamic_type: at::Tensor + name: result6 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: miopen_batch_norm + operator_name: miopen_batch_norm + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: running_mean + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: running_var + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: exponential_average_factor + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: epsilon + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -43286,7 +43759,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43401,7 +43874,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43526,7 +43999,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -44417,312 +44890,53 @@ with_gil: false deprecated: false has_math_kernel: true -- name: _sparse_sparse_matmul - operator_name: _sparse_sparse_matmul - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _sparse_mask_helper - operator_name: _sparse_mask_helper - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_sparse_mask_helper(Tensor t, Tensor mask_indices) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: t - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: mask_indices - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: t - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: mask_indices - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode - operator_name: mode - overload_name: '' +- name: _sparse_mm + operator_name: _sparse_mm + overload_name: reduce manual_kernel_registration: false category_override: '' - schema_string: aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) + schema_string: aten::_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self + name: sparse type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode_out - operator_name: mode - overload_name: values - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: dense type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool + dynamic_type: c10::string_view is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + name: reduce + type: c10::string_view + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode - operator_name: mode - overload_name: dimname - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self + name: sparse type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: dense type: const at::Tensor & - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool + dynamic_type: c10::string_view is_nullable: false - name: keepdim - type: bool + name: reduce + type: c10::string_view method_of: - Type - - Tensor - namespace mode: native - python_module: '' + python_module: sparse returns: - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor - - dynamic_type: at::Tensor - field_name: indices - name: indices + name: result type: at::Tensor inplace: false is_factory_method: false @@ -44731,106 +44945,375 @@ with_gil: false deprecated: false has_math_kernel: true -- name: mode_out - operator_name: mode - overload_name: dimname_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: mul - operator_name: mul - overload_name: Tensor +- name: _sparse_sparse_matmul + operator_name: _sparse_sparse_matmul + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mul.Tensor(Tensor self, Tensor other) -> Tensor + schema_string: aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode + operator_name: mode + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode_out + operator_name: mode + overload_name: values + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode + operator_name: mode + overload_name: dimname + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: mode_out + operator_name: mode + overload_name: dimname_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: mul + operator_name: mul + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::mul.Tensor(Tensor self, Tensor other) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -45712,7 +46195,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::narrow(Tensor(a) self, int dim, int start, int length) -> Tensor(a) + schema_string: aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -45778,7 +46261,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, int length) -> Tensor(a) + schema_string: aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -46103,6 +46586,494 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _native_batch_norm_legit + operator_name: _native_batch_norm_legit + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, at::Tensor &, at::Tensor &, bool, double, double) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit_out + operator_name: _native_batch_norm_legit + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!), Tensor(e!), Tensor(f!)) + arguments: + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, at::Tensor &, at::Tensor &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_mean + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_invstd + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit + operator_name: _native_batch_norm_legit + overload_name: no_stats + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, bool, double, double) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit_out + operator_name: _native_batch_norm_legit + overload_name: no_stats_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.no_stats_out(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_mean + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_invstd + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: batch_norm_stats operator_name: batch_norm_stats overload_name: '' @@ -47024,7 +47995,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, int[2] padding, int[2] stride=1) -> Tensor + schema_string: aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, int[2] stride=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -49165,7 +50136,7 @@ overload_name: names manual_kernel_registration: false category_override: '' - schema_string: aten::rand.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49247,7 +50218,7 @@ overload_name: generator_with_names manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_with_names(int[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49341,7 +50312,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::rand(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49411,7 +50382,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator(int[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49493,7 +50464,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -49542,7 +50513,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_out(int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -49687,7 +50658,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::randint(int high, int[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49767,7 +50738,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::randint.generator(int high, int[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49859,7 +50830,7 @@ overload_name: low manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low(int low, int high, int[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49949,7 +50920,7 @@ overload_name: low_generator manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_generator(int low, int high, int[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -50051,7 +51022,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.out(int high, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50110,7 +51081,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.generator_out(int high, int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50181,7 +51152,7 @@ overload_name: low_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_out(int low, int high, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50250,7 +51221,7 @@ overload_name: low_generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_generator_out(int low, int high, int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50529,7 +51500,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::randn(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50599,7 +51570,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator(int[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50681,7 +51652,7 @@ overload_name: names manual_kernel_registration: false category_override: '' - schema_string: aten::randn.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50763,7 +51734,7 @@ overload_name: generator_with_names manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_with_names(int[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50857,7 +51828,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50906,7 +51877,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_out(int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -52180,7 +53151,7 @@ overload_name: self_int manual_kernel_registration: false category_override: '' - schema_string: aten::repeat_interleave.self_int(Tensor self, int repeats, int? dim=None, *, int? output_size=None) -> Tensor + schema_string: aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, int? output_size=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -52293,6 +53264,51 @@ with_gil: false deprecated: false has_math_kernel: true +- name: _reshape_copy + operator_name: _reshape_copy + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_reshape_copy(Tensor self, SymInt[] size) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: _reshape_alias operator_name: _reshape_alias overload_name: '' @@ -53066,17 +54082,62 @@ type: at::Tensor inplace: false is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: _prelu_kernel + operator_name: _prelu_kernel + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_prelu_kernel(Tensor self, Tensor weight) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: prelu_backward - operator_name: prelu_backward +- name: _prelu_kernel_backward + operator_name: _prelu_kernel_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::prelu_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) + schema_string: aten::_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -53112,7 +54173,6 @@ type: const at::Tensor & method_of: - Type - - Tensor - namespace mode: native python_module: '' @@ -53884,7 +54944,7 @@ overload_name: int manual_kernel_registration: false category_override: '' - schema_string: aten::select.int(Tensor(a) self, int dim, int index) -> Tensor(a) + schema_string: aten::select.int(Tensor(a) self, int dim, SymInt index) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -53940,7 +55000,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, int index) -> Tensor + schema_string: aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -54005,7 +55065,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, int index) -> Tensor + schema_string: aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -55688,7 +56748,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_scatter(Tensor self, Tensor src, int dim, int index) -> Tensor + schema_string: aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -56417,7 +57477,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split.Tensor(Tensor self, int split_size, int dim=0) -> Tensor[] + schema_string: aten::unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -56475,7 +57535,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::split.Tensor(Tensor(a -> *) self, int split_size, int dim=0) -> Tensor(a)[] + schema_string: aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -56533,7 +57593,7 @@ overload_name: sizes manual_kernel_registration: false category_override: '' - schema_string: aten::split.sizes(Tensor(a -> *) self, int[] split_size, int dim=0) -> Tensor(a)[] + schema_string: aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -56591,7 +57651,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split_with_sizes(Tensor self, int[] split_sizes, int dim=0) -> Tensor[] + schema_string: aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -56649,7 +57709,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::split_with_sizes(Tensor(a -> *) self, int[] split_sizes, int dim=0) -> Tensor(a)[] + schema_string: aten::split_with_sizes(Tensor(a -> *) self, SymInt[] split_sizes, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -57106,6 +58166,52 @@ with_gil: false deprecated: false has_math_kernel: true +- name: squeeze + operator_name: squeeze + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a) + arguments: + - annotation: a + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: a + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: squeeze_ operator_name: squeeze_ overload_name: '' @@ -57186,6 +58292,51 @@ with_gil: false deprecated: false has_math_kernel: false +- name: squeeze_ + operator_name: squeeze_ + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!) + arguments: + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: self + type: at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: self + type: at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - Tensor + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: self + type: at::Tensor & + inplace: true + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: squeeze_ operator_name: squeeze_ overload_name: dimname @@ -59391,7 +60542,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::std.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -59399,12 +60550,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59425,12 +60578,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59589,7 +60744,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::std_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -59597,12 +60752,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59623,12 +60780,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59739,7 +60898,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::std_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -59753,6 +60912,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59779,6 +60939,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59900,7 +61061,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::std.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -59915,12 +61076,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59941,12 +61104,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60144,7 +61309,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::std.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -60158,6 +61323,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60184,6 +61350,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60218,7 +61385,7 @@ overload_name: correction_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -60239,6 +61406,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60265,6 +61433,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64030,7 +65199,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::var.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -64038,12 +65207,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64064,12 +65235,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64189,7 +65362,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::var.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -64204,12 +65377,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64230,12 +65405,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64433,7 +65610,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -64447,6 +65624,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64473,6 +65651,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64507,7 +65686,7 @@ overload_name: correction_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -64528,6 +65707,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64554,6 +65734,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64718,7 +65899,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::var_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -64726,12 +65907,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64752,12 +65935,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64868,7 +66053,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -64882,6 +66067,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64908,6 +66094,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -65205,6 +66392,7 @@ type: const at::Scalar & method_of: - Type + - Tensor - namespace mode: native python_module: '' @@ -68219,23 +69407,47 @@ has_math_kernel: false - name: frobenius_norm operator_name: frobenius_norm - overload_name: '' + overload_name: dim manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm(Tensor self) -> Tensor + schema_string: aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + size: 1 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + size: 1 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool method_of: - Type - namespace @@ -68252,13 +69464,20 @@ with_gil: false deprecated: false has_math_kernel: true -- name: frobenius_norm +- name: frobenius_norm_out operator_name: frobenius_norm - overload_name: dim + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor + schema_string: aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -68276,7 +69495,7 @@ is_nullable: false name: keepdim type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, bool) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -68295,6 +69514,60 @@ is_nullable: false name: keepdim type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: nuclear_norm + operator_name: nuclear_norm + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool method_of: - Type - namespace @@ -68311,12 +69584,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: frobenius_norm_out - operator_name: frobenius_norm +- name: nuclear_norm_out + operator_name: nuclear_norm overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -68330,133 +69603,13 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dim - size: 1 - type: at::IntArrayRef - annotation: null default: false dynamic_type: bool is_nullable: false name: keepdim type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dim - size: 1 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: nuclear_norm - operator_name: nuclear_norm - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: nuclear_norm_out - operator_name: nuclear_norm - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, bool, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -69995,20 +71148,30 @@ with_gil: false deprecated: false has_math_kernel: false -- name: addmm_out - operator_name: addmm - overload_name: out +- name: _sparse_mm_reduce_impl + operator_name: _sparse_mm_reduce_impl + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_mm_reduce_impl(Tensor self, Tensor other, str reduce) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, c10::string_view) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -70017,28 +71180,164 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: mat1 + name: other + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + method_of: + - Type + - namespace + mode: native + python_module: sparse + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _sparse_mm_reduce_impl_backward + operator_name: _sparse_mm_reduce_impl_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: mat2 + name: grad_out type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor is_nullable: false - kwarg_only: true - name: beta - type: const at::Scalar & + name: weight + type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: c10::string_view is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &) + name: reduce + type: c10::string_view + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: arg_out + type: const at::Tensor & + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const at::Tensor &, ::std::array) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: arg_out + type: const at::Tensor & + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + method_of: + - Type + - namespace + mode: native + python_module: sparse + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: addmm_out + operator_name: addmm + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: mat1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: mat2 + type: const at::Tensor & + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: beta + type: const at::Scalar & + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -72152,7 +73451,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -72703,7 +74002,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, int[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor + schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -74066,20 +75365,64 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse(Tensor self) -> Tensor + schema_string: aten::to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional, at::OptionalIntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74101,20 +75444,32 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csr(Tensor self) -> Tensor + schema_string: aten::to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74136,20 +75491,32 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csc(Tensor self) -> Tensor + schema_string: aten::to_sparse_csc(Tensor self, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74171,7 +75538,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsr(Tensor self, int[2] blocksize) -> Tensor + schema_string: aten::to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74184,7 +75551,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74197,6 +75570,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74218,7 +75597,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsc(Tensor self, int[2] blocksize) -> Tensor + schema_string: aten::to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74231,7 +75610,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74244,6 +75629,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74312,7 +75703,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_reorder_conv2d_weight(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1) -> Tensor + schema_string: aten::mkldnn_reorder_conv2d_weight(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, int[]? input_size=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74346,7 +75737,13 @@ is_nullable: false name: groups type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t) + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::OptionalIntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74380,6 +75777,12 @@ is_nullable: false name: groups type: int64_t + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef method_of: - Type - namespace @@ -77882,7 +79285,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_lstm_mps(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor, Tensor, Tensor) + schema_string: aten::_lstm_mps(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -77929,7 +79332,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -77997,6 +79400,9 @@ - dynamic_type: at::Tensor name: result4 type: at::Tensor + - dynamic_type: at::Tensor + name: result5 + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -78009,7 +79415,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::lstm_mps_backward(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[]) + schema_string: aten::lstm_mps_backward(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[]) arguments: - annotation: null dynamic_type: at::Tensor @@ -78041,6 +79447,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -78081,7 +79492,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple,::std::vector> (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) + schema_order_cpp_signature: ::std::tuple,::std::vector> (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -78113,6 +79524,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -80846,7 +82262,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pack_padded_sequence_backward(Tensor grad, int[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor + schema_string: aten::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -88647,180 +90063,125 @@ type: at::Tensor & inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: diag - operator_name: diag - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::diag(Tensor self, int diagonal=0) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: diag_backward - operator_name: diag_backward - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::diag_backward(Tensor grad, SymInt[] input_sizes, int diagonal) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_sizes - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_sizes - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: true -- name: cross_out - operator_name: cross - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: diag + operator_name: diag + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::diag(Tensor self, int diagonal=0) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: diagonal + type: int64_t + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: diagonal + type: int64_t + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: cross_out + operator_name: cross + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false abstract: false device_guard: true with_gil: false @@ -89327,7 +90688,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::trace_backward(Tensor grad, int[] sizes) -> Tensor + schema_string: aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -93066,7 +94427,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::index_select_backward(Tensor grad, int[] self_sizes, int dim, Tensor index) -> Tensor + schema_string: aten::index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -94338,7 +95699,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, float label_smoothing=0.0) -> Tensor + schema_string: aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, float label_smoothing=0.0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -94918,190 +96279,55 @@ with_gil: false deprecated: false has_math_kernel: true -- name: symeig_out - operator_name: symeig - overload_name: e +- name: svd_out + operator_name: svd + overload_name: U manual_kernel_registration: false category_override: '' - schema_string: aten::symeig.e(Tensor self, bool eigenvectors=False, bool upper=True, *, Tensor(a!) e, Tensor(b!) V) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) + schema_string: aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor - field_name: eigenvalues + field_name: U is_nullable: false - name: e + name: U output: true type: at::Tensor & - allocate: true annotation: b! dynamic_type: at::Tensor - field_name: eigenvectors - is_nullable: false - name: V - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: upper - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: eigenvalues + field_name: S is_nullable: false - name: e + name: S output: true type: at::Tensor & - allocate: true - annotation: b! + annotation: c! dynamic_type: at::Tensor - field_name: eigenvectors + field_name: V is_nullable: false name: V output: true type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: eigenvalues - name: e - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: eigenvectors - name: V - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: symeig - operator_name: symeig - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::symeig(Tensor self, bool eigenvectors=False, bool upper=True) -> (Tensor eigenvalues, Tensor eigenvectors) - arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - annotation: null default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors + name: some type: bool - annotation: null default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: eigenvalues - name: eigenvalues - type: at::Tensor - - dynamic_type: at::Tensor - field_name: eigenvectors - name: eigenvectors_return - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _symeig_helper - operator_name: _symeig_helper - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_symeig_helper(Tensor self, bool eigenvectors, bool upper) -> (Tensor, Tensor) - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper + name: compute_uv type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -95109,100 +96335,16 @@ name: self type: const at::Tensor & - annotation: null + default: true dynamic_type: bool is_nullable: false - name: eigenvectors + name: some type: bool - annotation: null + default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result0 - type: at::Tensor - - dynamic_type: at::Tensor - name: result1 - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: svd_out - operator_name: svd - overload_name: U - manual_kernel_registration: false - category_override: '' - schema_string: aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: U - is_nullable: false - name: U - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: S - is_nullable: false - name: S - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - field_name: V - is_nullable: false - name: V - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: some - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: compute_uv - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: some - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: compute_uv + name: compute_uv type: bool - allocate: true annotation: a! @@ -101246,45 +102388,48 @@ with_gil: false deprecated: false has_math_kernel: true -- name: minimum - operator_name: minimum - overload_name: '' +- name: max_out + operator_name: max + overload_name: unary_out manual_kernel_registration: false category_override: '' - schema_string: aten::minimum(Tensor self, Tensor other) -> Tensor + schema_string: aten::max.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - - annotation: null + - allocate: true + annotation: a! dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & + name: out + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: other + name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null + - allocate: true + annotation: a! dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Tensor & + name: out + output: true + type: at::Tensor & method_of: - Type - - Tensor - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: result - type: at::Tensor + name: out + type: at::Tensor & inplace: false is_factory_method: false abstract: true @@ -101292,20 +102437,13 @@ with_gil: false deprecated: false has_math_kernel: false -- name: minimum_out +- name: minimum operator_name: minimum - overload_name: out + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::minimum(Tensor self, Tensor other) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -101316,7 +102454,7 @@ is_nullable: false name: other type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101328,22 +102466,16 @@ is_nullable: false name: other type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type + - Tensor - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -101351,12 +102483,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: min_out - operator_name: min +- name: minimum_out + operator_name: minimum overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101405,147 +102537,17 @@ type: at::Tensor & inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true -- name: min + has_math_kernel: false +- name: min_out operator_name: min - overload_name: other - manual_kernel_registration: false - category_override: '' - schema_string: aten::min.other(Tensor self, Tensor other) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: quantile - operator_name: quantile - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: q - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: q - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: quantile_out - operator_name: quantile overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101562,28 +102564,9 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: q + name: other type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101593,27 +102576,8 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: q + name: other type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - allocate: true annotation: a! dynamic_type: at::Tensor @@ -101637,12 +102601,58 @@ with_gil: false deprecated: false has_math_kernel: true +- name: min + operator_name: min + overload_name: other + manual_kernel_registration: false + category_override: '' + schema_string: aten::min.other(Tensor self, Tensor other) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true - name: quantile operator_name: quantile - overload_name: scalar + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -101650,10 +102660,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101673,7 +102683,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101681,10 +102691,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101723,10 +102733,10 @@ has_math_kernel: true - name: quantile_out operator_name: quantile - overload_name: scalar_out + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101741,10 +102751,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101764,7 +102774,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101772,10 +102782,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101818,12 +102828,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: nanquantile - operator_name: nanquantile - overload_name: '' +- name: quantile + operator_name: quantile + overload_name: scalar manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -101831,10 +102841,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101854,7 +102864,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101862,10 +102872,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101902,12 +102912,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: nanquantile_out - operator_name: nanquantile - overload_name: out +- name: quantile_out + operator_name: quantile + overload_name: scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101922,10 +102932,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101945,7 +102955,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101953,10 +102963,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102001,10 +103011,10 @@ has_math_kernel: true - name: nanquantile operator_name: nanquantile - overload_name: scalar + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -102012,10 +103022,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102035,7 +103045,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102043,10 +103053,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102085,10 +103095,10 @@ has_math_kernel: true - name: nanquantile_out operator_name: nanquantile - overload_name: scalar_out + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -102103,10 +103113,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102126,7 +103136,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102134,10 +103144,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102180,27 +103190,102 @@ with_gil: false deprecated: false has_math_kernel: true -- name: sort_out - operator_name: sort - overload_name: values +- name: nanquantile + operator_name: nanquantile + overload_name: scalar manual_kernel_registration: false category_override: '' - schema_string: aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + schema_string: aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor - field_name: values is_nullable: false - name: values - output: true - type: at::Tensor & + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: double + is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: double + is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: nanquantile_out + operator_name: nanquantile + overload_name: scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + arguments: - allocate: true - annotation: b! + annotation: a! dynamic_type: at::Tensor - field_name: indices is_nullable: false - name: indices + name: out output: true type: at::Tensor & - annotation: null @@ -102209,18 +103294,30 @@ name: self type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t + dynamic_type: double is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true name: dim - type: int64_t + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: descending + name: keepdim type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102228,31 +103325,34 @@ name: self type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t + dynamic_type: double is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true name: dim - type: int64_t + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: descending + name: keepdim type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view is_nullable: false - name: values - output: true - type: at::Tensor & + kwarg_only: true + name: interpolation + type: c10::string_view - allocate: true - annotation: b! + annotation: a! dynamic_type: at::Tensor - field_name: indices is_nullable: false - name: indices + name: out output: true type: at::Tensor & method_of: @@ -102262,26 +103362,117 @@ python_module: '' returns: - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices + name: out type: at::Tensor & inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: sort_out operator_name: sort - overload_name: values_stable + overload_name: values manual_kernel_registration: false category_override: '' - schema_string: aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + schema_string: aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: descending + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: descending + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: sort_out + operator_name: sort + overload_name: values_stable + manual_kernel_registration: false + category_override: '' + schema_string: aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) arguments: - allocate: true annotation: a! @@ -103814,7 +105005,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::unfold_backward(Tensor grad_in, int[] input_sizes, int dim, int size, int step) -> Tensor + schema_string: aten::unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -105289,7 +106480,7 @@ overload_name: float_float manual_kernel_registration: false category_override: '' - schema_string: aten::normal.float_float(float mean, float std, int[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::normal.float_float(float mean, float std, SymInt[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: double @@ -105393,7 +106584,7 @@ overload_name: float_float_out manual_kernel_registration: false category_override: '' - schema_string: aten::normal.float_float_out(float mean, float std, int[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::normal.float_float_out(float mean, float std, SymInt[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -105992,48 +107183,121 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add - operator_name: _foreach_add - overload_name: List +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + schema_string: aten::_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type @@ -106051,12 +107315,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_ - operator_name: _foreach_add_ - overload_name: List +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + schema_string: aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106064,91 +107328,150 @@ name: self type: at::TensorList - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) - schema_order_arguments: - - annotation: a! + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_maximum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type - namespace mode: native python_module: '' - returns: [] - inplace: true + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub - operator_name: _foreach_sub - overload_name: List +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + schema_string: aten::_foreach_maximum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) - schema_order_arguments: + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type @@ -106166,18 +107489,60 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_ - operator_name: _foreach_sub_ - overload_name: List +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + schema_string: aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add + operator_name: _foreach_add + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -106190,9 +107555,68 @@ kwarg_only: true name: alpha type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: a! + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add_ + operator_name: _foreach_add_ + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -106222,12 +107646,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul - operator_name: _foreach_mul +- name: _foreach_sub + operator_name: _foreach_sub overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106239,7 +107663,14 @@ is_nullable: false name: other type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106251,6 +107682,13 @@ is_nullable: false name: other type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & method_of: - Type - namespace @@ -106267,12 +107705,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_ - operator_name: _foreach_mul_ +- name: _foreach_sub_ + operator_name: _foreach_sub_ overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106284,7 +107722,14 @@ is_nullable: false name: other type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106296,6 +107741,13 @@ is_nullable: false name: other type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & method_of: - Type - namespace @@ -106309,12 +107761,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div - operator_name: _foreach_div +- name: _foreach_mul + operator_name: _foreach_mul overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106354,12 +107806,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_ - operator_name: _foreach_div_ +- name: _foreach_mul_ + operator_name: _foreach_mul_ overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106396,12 +107848,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add - operator_name: _foreach_add - overload_name: ScalarList +- name: _foreach_div + operator_name: _foreach_div + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106409,11 +107861,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106421,10 +107873,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106441,12 +107893,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_ - operator_name: _foreach_add_ - overload_name: ScalarList +- name: _foreach_div_ + operator_name: _foreach_div_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106454,11 +107906,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106466,10 +107918,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106483,12 +107935,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub - operator_name: _foreach_sub - overload_name: ScalarList +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106496,11 +107948,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106508,10 +107960,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106528,12 +107980,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_ - operator_name: _foreach_sub_ - overload_name: ScalarList +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106541,11 +107993,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106553,10 +108005,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106570,12 +108022,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div - operator_name: _foreach_div - overload_name: ScalarList +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106583,11 +108035,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106595,10 +108047,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106615,12 +108067,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_ - operator_name: _foreach_div_ - overload_name: ScalarList +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106628,11 +108080,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106640,10 +108092,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106657,12 +108109,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul - operator_name: _foreach_mul - overload_name: ScalarList +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106670,11 +108122,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106682,10 +108134,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106702,12 +108154,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_ - operator_name: _foreach_mul_ - overload_name: ScalarList +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106715,11 +108167,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106727,10 +108179,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106744,25 +108196,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_exp - operator_name: _foreach_exp - overload_name: '' +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_exp(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList method_of: - Type - namespace @@ -106779,56 +108241,34 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_zero_ - operator_name: _foreach_zero_ - overload_name: '' +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_zero_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false - name: self + name: other type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_exp_ - operator_name: _foreach_exp_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_exp_(Tensor(a!)[] self) -> () - arguments: + schema_order_cpp_signature: void (at::TensorList, at::TensorList) + schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false - name: self + name: other type: at::TensorList method_of: - Type @@ -106843,25 +108283,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sqrt - operator_name: _foreach_sqrt - overload_name: '' +- name: _foreach_add + operator_name: _foreach_add + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sqrt(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106878,25 +108328,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sqrt_ - operator_name: _foreach_sqrt_ - overload_name: '' +- name: _foreach_add_ + operator_name: _foreach_add_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sqrt_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106910,25 +108370,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_abs - operator_name: _foreach_abs - overload_name: '' +- name: _foreach_sub + operator_name: _foreach_sub + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_abs(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106945,25 +108415,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_abs_ - operator_name: _foreach_abs_ - overload_name: '' +- name: _foreach_sub_ + operator_name: _foreach_sub_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_abs_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106977,25 +108457,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_acos - operator_name: _foreach_acos - overload_name: '' +- name: _foreach_div + operator_name: _foreach_div + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_acos(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107012,25 +108502,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_acos_ - operator_name: _foreach_acos_ - overload_name: '' +- name: _foreach_div_ + operator_name: _foreach_div_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_acos_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107044,25 +108544,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_asin - operator_name: _foreach_asin - overload_name: '' +- name: _foreach_mul + operator_name: _foreach_mul + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_asin(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107079,25 +108589,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_asin_ - operator_name: _foreach_asin_ - overload_name: '' +- name: _foreach_mul_ + operator_name: _foreach_mul_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_asin_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107111,25 +108631,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_atan - operator_name: _foreach_atan - overload_name: '' +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_atan(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107146,25 +108676,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_atan_ - operator_name: _foreach_atan_ - overload_name: '' +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_atan_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107178,25 +108718,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_ceil - operator_name: _foreach_ceil - overload_name: '' +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_ceil(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107213,25 +108763,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_ceil_ - operator_name: _foreach_ceil_ - overload_name: '' +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_ceil_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107245,25 +108805,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cos - operator_name: _foreach_cos - overload_name: '' +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cos(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_maximum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107280,25 +108850,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cos_ - operator_name: _foreach_cos_ - overload_name: '' +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cos_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_maximum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107312,25 +108892,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cosh - operator_name: _foreach_cosh - overload_name: '' +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cosh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107347,25 +108937,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cosh_ - operator_name: _foreach_cosh_ - overload_name: '' +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cosh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107379,12 +108979,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erf - operator_name: _foreach_erf +- name: _foreach_exp + operator_name: _foreach_exp overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erf(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_exp(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107414,12 +109014,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erf_ - operator_name: _foreach_erf_ +- name: _foreach_zero_ + operator_name: _foreach_zero_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erf_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_zero_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107446,47 +109046,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erfc - operator_name: _foreach_erfc - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_erfc(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_erfc_ - operator_name: _foreach_erfc_ +- name: _foreach_exp_ + operator_name: _foreach_exp_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erfc_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_exp_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107513,12 +109078,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_expm1 - operator_name: _foreach_expm1 +- name: _foreach_sqrt + operator_name: _foreach_sqrt overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_expm1(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_sqrt(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107548,12 +109113,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_expm1_ - operator_name: _foreach_expm1_ +- name: _foreach_sqrt_ + operator_name: _foreach_sqrt_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_expm1_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_sqrt_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107580,12 +109145,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_floor - operator_name: _foreach_floor +- name: _foreach_abs + operator_name: _foreach_abs overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_floor(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_abs(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107615,12 +109180,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_floor_ - operator_name: _foreach_floor_ +- name: _foreach_abs_ + operator_name: _foreach_abs_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_floor_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_abs_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107647,12 +109212,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log - operator_name: _foreach_log +- name: _foreach_acos + operator_name: _foreach_acos overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_acos(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107682,146 +109247,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log_ - operator_name: _foreach_log_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log_(Tensor(a!)[] self) -> () - arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log10 - operator_name: _foreach_log10 - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log10(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log10_ - operator_name: _foreach_log10_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log10_(Tensor(a!)[] self) -> () - arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log1p - operator_name: _foreach_log1p - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log1p(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log1p_ - operator_name: _foreach_log1p_ +- name: _foreach_acos_ + operator_name: _foreach_acos_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log1p_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_acos_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107848,12 +109279,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log2 - operator_name: _foreach_log2 +- name: _foreach_asin + operator_name: _foreach_asin overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log2(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_asin(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107883,12 +109314,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log2_ - operator_name: _foreach_log2_ +- name: _foreach_asin_ + operator_name: _foreach_asin_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log2_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_asin_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107915,12 +109346,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_neg - operator_name: _foreach_neg +- name: _foreach_atan + operator_name: _foreach_atan overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_neg(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_atan(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107950,12 +109381,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_neg_ - operator_name: _foreach_neg_ +- name: _foreach_atan_ + operator_name: _foreach_atan_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_neg_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_atan_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107982,12 +109413,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tan - operator_name: _foreach_tan +- name: _foreach_ceil + operator_name: _foreach_ceil overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tan(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_ceil(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108017,12 +109448,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tan_ - operator_name: _foreach_tan_ +- name: _foreach_ceil_ + operator_name: _foreach_ceil_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tan_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_ceil_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108049,12 +109480,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tanh - operator_name: _foreach_tanh +- name: _foreach_cos + operator_name: _foreach_cos overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tanh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_cos(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108084,12 +109515,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tanh_ - operator_name: _foreach_tanh_ +- name: _foreach_cos_ + operator_name: _foreach_cos_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tanh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_cos_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108116,12 +109547,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sin - operator_name: _foreach_sin +- name: _foreach_cosh + operator_name: _foreach_cosh overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sin(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_cosh(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108151,12 +109582,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sin_ - operator_name: _foreach_sin_ +- name: _foreach_cosh_ + operator_name: _foreach_cosh_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sin_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_cosh_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108183,12 +109614,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sinh - operator_name: _foreach_sinh +- name: _foreach_erf + operator_name: _foreach_erf overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sinh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_erf(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108218,12 +109649,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sinh_ - operator_name: _foreach_sinh_ +- name: _foreach_erf_ + operator_name: _foreach_erf_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sinh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_erf_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108250,12 +109681,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_round - operator_name: _foreach_round +- name: _foreach_erfc + operator_name: _foreach_erfc overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_round(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_erfc(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108285,12 +109716,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_round_ - operator_name: _foreach_round_ +- name: _foreach_erfc_ + operator_name: _foreach_erfc_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_round_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_erfc_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108317,12 +109748,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_lgamma - operator_name: _foreach_lgamma +- name: _foreach_expm1 + operator_name: _foreach_expm1 overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_lgamma(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_expm1(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108352,12 +109783,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_lgamma_ - operator_name: _foreach_lgamma_ +- name: _foreach_expm1_ + operator_name: _foreach_expm1_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_lgamma_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_expm1_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108384,12 +109815,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_frac - operator_name: _foreach_frac +- name: _foreach_floor + operator_name: _foreach_floor overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_frac(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_floor(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108419,12 +109850,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_frac_ - operator_name: _foreach_frac_ +- name: _foreach_floor_ + operator_name: _foreach_floor_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_frac_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_floor_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108451,12 +109882,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_reciprocal - operator_name: _foreach_reciprocal +- name: _foreach_log + operator_name: _foreach_log overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108486,12 +109917,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_reciprocal_ - operator_name: _foreach_reciprocal_ +- name: _foreach_log_ + operator_name: _foreach_log_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108518,12 +109949,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sigmoid - operator_name: _foreach_sigmoid +- name: _foreach_log10 + operator_name: _foreach_log10 overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log10(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108553,12 +109984,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sigmoid_ - operator_name: _foreach_sigmoid_ +- name: _foreach_log10_ + operator_name: _foreach_log10_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log10_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108585,12 +110016,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_trunc - operator_name: _foreach_trunc +- name: _foreach_log1p + operator_name: _foreach_log1p overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_trunc(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log1p(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108620,12 +110051,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_trunc_ - operator_name: _foreach_trunc_ +- name: _foreach_log1p_ + operator_name: _foreach_log1p_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_trunc_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log1p_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108652,57 +110083,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv_ - operator_name: _foreach_addcdiv_ - overload_name: Scalar +- name: _foreach_log2 + operator_name: _foreach_log2 + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () + schema_string: aten::_foreach_log2(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_log2_ + operator_name: _foreach_log2_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_log2_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_neg + operator_name: _foreach_neg + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_neg(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_neg_ + operator_name: _foreach_neg_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_neg_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tan + operator_name: _foreach_tan + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tan(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tan_ + operator_name: _foreach_tan_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tan_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108716,57 +110284,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul_ - operator_name: _foreach_addcmul_ - overload_name: Scalar +- name: _foreach_tanh + operator_name: _foreach_tanh + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () + schema_string: aten::_foreach_tanh(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tanh_ + operator_name: _foreach_tanh_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tanh_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sin + operator_name: _foreach_sin + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sin(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sin_ + operator_name: _foreach_sin_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sin_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sinh + operator_name: _foreach_sinh + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sinh(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sinh_ + operator_name: _foreach_sinh_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sinh_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108780,55 +110485,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv_ - operator_name: _foreach_addcdiv_ - overload_name: ScalarList +- name: _foreach_round + operator_name: _foreach_round + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () + schema_string: aten::_foreach_round(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_round_ + operator_name: _foreach_round_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_round_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lgamma + operator_name: _foreach_lgamma + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lgamma(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lgamma_ + operator_name: _foreach_lgamma_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lgamma_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_frac + operator_name: _foreach_frac + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_frac(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - dynamic_type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_frac_ + operator_name: _foreach_frac_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_frac_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108842,55 +110686,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul_ - operator_name: _foreach_addcmul_ - overload_name: ScalarList +- name: _foreach_reciprocal + operator_name: _foreach_reciprocal + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () + schema_string: aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_reciprocal_ + operator_name: _foreach_reciprocal_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sigmoid + operator_name: _foreach_sigmoid + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sigmoid_ + operator_name: _foreach_sigmoid_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_trunc + operator_name: _foreach_trunc + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_trunc(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - dynamic_type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_trunc_ + operator_name: _foreach_trunc_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_trunc_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108904,14 +110887,14 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv - operator_name: _foreach_addcdiv +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108932,9 +110915,9 @@ is_nullable: false name: value type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108960,25 +110943,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul - operator_name: _foreach_addcmul +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] + schema_string: aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108999,9 +110979,9 @@ is_nullable: false name: value type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109027,25 +111007,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv - operator_name: _foreach_addcdiv +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109065,9 +111042,9 @@ is_nullable: false name: scalars type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109092,25 +111069,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul - operator_name: _foreach_addcmul - overload_name: ScalarList +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ + overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109126,13 +111100,13 @@ name: tensor2 type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::Tensor is_nullable: false name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109148,34 +111122,31 @@ name: tensor2 type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::Tensor is_nullable: false name: scalars - type: at::ArrayRef + type: const at::Tensor & method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum - operator_name: _foreach_maximum - overload_name: List +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109183,11 +111154,21 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) - schema_order_arguments: - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109195,30 +111176,37 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum_ - operator_name: _foreach_maximum_ - overload_name: List +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ + overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_addcmul_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -109228,9 +111216,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -109240,8 +111238,18 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & method_of: - Type - namespace @@ -109255,12 +111263,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum - operator_name: _foreach_minimum - overload_name: List +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -109270,9 +111278,20 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -109282,8 +111301,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & method_of: - Type - namespace @@ -109300,14 +111330,14 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum_ - operator_name: _foreach_minimum_ - overload_name: List +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self @@ -109315,11 +111345,22 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self @@ -109327,27 +111368,41 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & method_of: - Type - namespace mode: native python_module: '' - returns: [] - inplace: true + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_norm - operator_name: _foreach_norm - overload_name: Scalar +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] + schema_string: aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -109355,12 +111410,21 @@ name: self type: at::TensorList - annotation: null - default: 2 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: ord - type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -109368,11 +111432,20 @@ name: self type: at::TensorList - annotation: null - default: 2 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: ord - type: const at::Scalar & + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -109389,41 +111462,497 @@ with_gil: false deprecated: false has_math_kernel: false -- name: bucketize - operator_name: bucketize +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor + schema_string: aten::_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: self - type: const at::Tensor & + type: at::TensorList - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: boundaries - type: const at::Tensor & + name: tensor1 + type: at::TensorList - annotation: null - default: false - dynamic_type: bool + dynamic_type: at::TensorList is_nullable: false - kwarg_only: true - name: out_int32 - type: bool + name: tensor2 + type: at::TensorList - annotation: null - default: false - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - kwarg_only: true - name: right - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool) + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: ScalarList + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcmul.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_norm + operator_name: _foreach_norm + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp + operator_name: _foreach_lerp + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_ + operator_name: _foreach_lerp_ + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp + operator_name: _foreach_lerp + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_ + operator_name: _foreach_lerp_ + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: bucketize + operator_name: bucketize + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: boundaries + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: out_int32 + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: right + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & @@ -109723,41 +112252,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _torch_cuda_cu_linker_symbol_op - operator_name: _torch_cuda_cu_linker_symbol_op - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_torch_cuda_cu_linker_symbol_op(Tensor self) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false - name: searchsorted_out operator_name: searchsorted overload_name: Tensor_out @@ -111450,7 +113944,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nll_loss.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -111545,7 +114039,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_nd(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss_nd(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -111626,7 +114120,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -111707,7 +114201,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -111813,7 +114307,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight) + schema_string: aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) arguments: - annotation: null dynamic_type: at::Tensor @@ -111893,7 +114387,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112002,7 +114496,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight) -> Tensor + schema_string: aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -112097,7 +114591,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112192,7 +114686,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -112273,7 +114767,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -112379,7 +114873,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight) + schema_string: aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) arguments: - annotation: null dynamic_type: at::Tensor @@ -112459,7 +114953,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112568,7 +115062,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight) -> Tensor + schema_string: aten::nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -116944,7 +119438,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::adaptive_avg_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -117005,7 +119499,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::adaptive_avg_pool3d(Tensor self, int[3] output_size) -> Tensor + schema_string: aten::adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -117052,7 +119546,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_adaptive_avg_pool3d(Tensor self, int[3] output_size) -> Tensor + schema_string: aten::_adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120595,7 +123089,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d.out(Tensor self, int[2] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120656,7 +123150,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d(Tensor self, int[2] padding) -> Tensor + schema_string: aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120703,7 +123197,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, int[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120774,7 +123268,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, int[2] padding) -> Tensor + schema_string: aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120831,7 +123325,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d.out(Tensor self, int[4] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120892,7 +123386,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d(Tensor self, int[4] padding) -> Tensor + schema_string: aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120939,7 +123433,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, int[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121010,7 +123504,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, int[4] padding) -> Tensor + schema_string: aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121067,7 +123561,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d.out(Tensor self, int[6] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121128,7 +123622,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d(Tensor self, int[6] padding) -> Tensor + schema_string: aten::reflection_pad3d(Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121175,7 +123669,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, int[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121246,7 +123740,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d_backward(Tensor grad_output, Tensor self, int[6] padding) -> Tensor + schema_string: aten::reflection_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121303,7 +123797,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d.out(Tensor self, int[2] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121364,7 +123858,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d(Tensor self, int[2] padding) -> Tensor + schema_string: aten::replication_pad1d(Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121411,7 +123905,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, int[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121482,7 +123976,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d_backward(Tensor grad_output, Tensor self, int[2] padding) -> Tensor + schema_string: aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121539,7 +124033,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d.out(Tensor self, int[4] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121600,7 +124094,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d(Tensor self, int[4] padding) -> Tensor + schema_string: aten::replication_pad2d(Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121647,7 +124141,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d_backward.grad_input(Tensor grad_output, Tensor self, int[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121718,7 +124212,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d_backward(Tensor grad_output, Tensor self, int[4] padding) -> Tensor + schema_string: aten::replication_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121775,7 +124269,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d.out(Tensor self, int[6] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121836,7 +124330,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d(Tensor self, int[6] padding) -> Tensor + schema_string: aten::replication_pad3d(Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121883,7 +124377,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, int[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121954,7 +124448,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d_backward(Tensor grad_output, Tensor self, int[6] padding) -> Tensor + schema_string: aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122011,7 +124505,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pad_circular(Tensor self, int[] pad) -> Tensor + schema_string: aten::_pad_circular(Tensor self, SymInt[] pad) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122056,7 +124550,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pad_enum(Tensor self, int[] pad, int mode, float? value=None) -> Tensor + schema_string: aten::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122123,7 +124617,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::pad(Tensor self, int[] pad, str mode="constant", float? value=None) -> Tensor + schema_string: aten::pad(Tensor self, SymInt[] pad, str mode="constant", float? value=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122247,86 +124741,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_linear1d_backward - operator_name: upsample_linear1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_linear1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: upsample_bilinear2d operator_name: upsample_bilinear2d overload_name: vec @@ -122387,33 +124806,28 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bilinear2d_backward - operator_name: upsample_bilinear2d_backward + has_math_kernel: true +- name: _upsample_bilinear2d_aa + operator_name: _upsample_bilinear2d_aa overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122424,23 +124838,18 @@ is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122462,17 +124871,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bilinear2d_aa - operator_name: _upsample_bilinear2d_aa + has_math_kernel: true +- name: upsample_trilinear3d + operator_name: upsample_trilinear3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122527,33 +124936,28 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bilinear2d_aa_backward - operator_name: _upsample_bilinear2d_aa_backward + has_math_kernel: true +- name: upsample_bicubic2d + operator_name: upsample_bicubic2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122564,23 +124968,18 @@ is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122602,17 +125001,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_trilinear3d - operator_name: upsample_trilinear3d + has_math_kernel: true +- name: _upsample_bicubic2d_aa + operator_name: _upsample_bicubic2d_aa overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122667,65 +125066,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_trilinear3d_backward - operator_name: upsample_trilinear3d_backward + has_math_kernel: true +- name: upsample_nearest1d + operator_name: upsample_nearest1d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122742,17 +125121,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bicubic2d - operator_name: upsample_bicubic2d + has_math_kernel: true +- name: _upsample_nearest_exact1d + operator_name: _upsample_nearest_exact1d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122764,17 +125143,12 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -122786,11 +125160,6 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122807,65 +125176,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bicubic2d_backward - operator_name: upsample_bicubic2d_backward + has_math_kernel: true +- name: upsample_nearest2d + operator_name: upsample_nearest2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122882,17 +125231,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bicubic2d_aa - operator_name: _upsample_bicubic2d_aa + has_math_kernel: true +- name: _upsample_nearest_exact2d + operator_name: _upsample_nearest_exact2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122904,17 +125253,12 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -122926,11 +125270,6 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122947,65 +125286,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bicubic2d_aa_backward - operator_name: _upsample_bicubic2d_aa_backward + has_math_kernel: true +- name: upsample_nearest3d + operator_name: upsample_nearest3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -123022,17 +125341,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_nearest1d - operator_name: upsample_nearest1d + has_math_kernel: true +- name: _upsample_nearest_exact3d + operator_name: _upsample_nearest_exact3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -123077,676 +125396,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact1d - operator_name: _upsample_nearest_exact1d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest1d_backward - operator_name: upsample_nearest1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact1d_backward - operator_name: _upsample_nearest_exact1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest2d - operator_name: upsample_nearest2d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact2d - operator_name: _upsample_nearest_exact2d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest2d_backward - operator_name: upsample_nearest2d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact2d_backward - operator_name: _upsample_nearest_exact2d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest3d - operator_name: upsample_nearest3d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact3d - operator_name: _upsample_nearest_exact3d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest3d_backward - operator_name: upsample_nearest3d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact3d_backward - operator_name: _upsample_nearest_exact3d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: upsample_linear1d_out operator_name: upsample_linear1d overload_name: out @@ -128360,7 +130014,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -128499,7 +130153,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int[2] dilation=1) -> Tensor + schema_string: aten::slow_conv_transpose2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, int[2] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -128624,7 +130278,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -128763,7 +130417,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int[3] dilation=1) -> Tensor + schema_string: aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129541,7 +131195,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_conv_depthwise2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, int[2] dilation, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_conv_depthwise2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, SymInt[2] padding, int[2] dilation, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -129658,7 +131312,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_conv_depthwise2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, int[2] dilation) -> Tensor + schema_string: aten::_conv_depthwise2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, SymInt[2] padding, int[2] dilation) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129761,7 +131415,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::conv_depthwise3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, int[3] dilation) -> Tensor + schema_string: aten::conv_depthwise3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, int[3] dilation) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129864,7 +131518,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -129975,7 +131629,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0) -> Tensor + schema_string: aten::slow_conv3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130072,7 +131726,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, *, Tensor(a!) output) -> Tensor(a!) + schema_string: aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, *, Tensor(a!) output) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -130177,7 +131831,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding) -> Tensor + schema_string: aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130268,7 +131922,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1) -> Tensor + schema_string: aten::slow_conv_dilated2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, int[2] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130379,7 +132033,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1) -> Tensor + schema_string: aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -147845,7 +149499,7 @@ overload_name: int manual_kernel_registration: false category_override: '' - schema_string: aten::select_copy.int(Tensor self, int dim, int index) -> Tensor + schema_string: aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -148018,7 +149672,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::split_copy.Tensor(Tensor self, int split_size, int dim=0) -> Tensor[] + schema_string: aten::split_copy.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -148075,7 +149729,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::split_with_sizes_copy(Tensor self, int[] split_sizes, int dim=0) -> Tensor[] + schema_string: aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -148207,6 +149861,51 @@ with_gil: false deprecated: false has_math_kernel: false +- name: squeeze_copy + operator_name: squeeze_copy + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze_copy.dims(Tensor self, int[] dim) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: t_copy operator_name: t_copy overload_name: '' @@ -148669,221 +150368,32 @@ with_gil: false deprecated: false has_math_kernel: false -- name: view_copy - operator_name: view_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy(Tensor self, SymInt[] size) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_copy - operator_name: view_copy - overload_name: dtype - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::ScalarType) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unfold_copy - operator_name: unfold_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dimension - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: size - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dimension - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: size - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: alias_copy - operator_name: alias_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::alias_copy(Tensor self) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _fw_primal_copy_out - operator_name: _fw_primal_copy - overload_name: out +- name: unbind_copy_out + operator_name: unbind_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) + schema_order_cpp_signature: void (const at::Tensor &, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -148891,26 +150401,24 @@ name: self type: const at::Tensor & - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -148918,117 +150426,67 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _make_dual_copy_out - operator_name: _make_dual_copy - overload_name: out +- name: split_copy_out + operator_name: split_copy + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::split_copy.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false - name: primal + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: int64_t is_nullable: false - name: tangent - type: const at::Tensor & + name: split_size + type: int64_t - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &) + schema_order_cpp_signature: void (const at::Tensor &, int64_t, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: primal - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: tangent + name: self type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: level + name: split_size type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_as_real_copy_out - operator_name: view_as_real_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & + name: dim + type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -149036,146 +150494,67 @@ with_gil: false deprecated: false has_math_kernel: false -- name: view_as_complex_copy_out - operator_name: view_as_complex_copy +- name: split_with_sizes_copy_out + operator_name: split_with_sizes_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _conj_copy_out - operator_name: _conj_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::IntArrayRef is_nullable: false - name: out - output: true - type: at::Tensor & + name: split_sizes + type: at::IntArrayRef - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + name: dim + type: int64_t + schema_order_cpp_signature: void (const at::Tensor &, at::IntArrayRef, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _neg_view_copy_out - operator_name: _neg_view_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::IntArrayRef is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + name: split_sizes + type: at::IntArrayRef - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & + name: dim + type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -149183,20 +150562,13 @@ with_gil: false deprecated: false has_math_kernel: false -- name: as_strided_copy_out - operator_name: as_strided_copy - overload_name: out +- name: view_copy + operator_name: view_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy(Tensor self, SymInt[] size) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -149207,18 +150579,7 @@ is_nullable: false name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: storage_offset - type: c10::optional - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149230,24 +150591,6 @@ is_nullable: false name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: storage_offset - type: c10::optional - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149255,8 +150598,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149264,31 +150607,24 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _sparse_broadcast_to_copy_out - operator_name: _sparse_broadcast_to_copy - overload_name: out +- name: view_copy + operator_name: view_copy + overload_name: dtype manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::ScalarType is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + name: dtype + type: at::ScalarType + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::ScalarType) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149296,17 +150632,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::ScalarType is_nullable: false - name: out - output: true - type: at::Tensor & + name: dtype + type: at::ScalarType method_of: - Type - namespace @@ -149314,8 +150643,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149323,44 +150652,34 @@ with_gil: false deprecated: false has_math_kernel: false -- name: diagonal_copy_out - operator_name: diagonal_copy - overload_name: out +- name: unfold_copy + operator_name: unfold_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: offset + name: dimension type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim1 + name: size type: int64_t - annotation: null - default: 1 dynamic_type: int64_t is_nullable: false - name: dim2 + name: step type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149368,30 +150687,20 @@ name: self type: const at::Tensor & - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: offset + name: dimension type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim1 + name: size type: int64_t - annotation: null - default: 1 dynamic_type: int64_t is_nullable: false - name: dim2 + name: step type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149399,8 +150708,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149408,63 +150717,25 @@ with_gil: false deprecated: false has_math_kernel: false -- name: expand_copy_out - operator_name: expand_copy - overload_name: out +- name: alias_copy + operator_name: alias_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::alias_copy(Tensor self) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: implicit - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: implicit - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149472,8 +150743,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149481,31 +150752,30 @@ with_gil: false deprecated: false has_math_kernel: false -- name: permute_copy_out - operator_name: permute_copy - overload_name: out +- name: to_padded_tensor + operator_name: to_padded_tensor + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: double is_nullable: false - name: dims - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + name: padding + type: double + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: output_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149513,26 +150783,25 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dims - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false - name: out - output: true - type: at::Tensor & + name: padding + type: double + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: output_size + type: at::OptionalIntArrayRef method_of: - Type - - namespace + - Tensor mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149540,36 +150809,24 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _reshape_alias_copy_out - operator_name: _reshape_alias_copy - overload_name: out +- name: _nested_tensor_softmax_with_shape + operator_name: _nested_tensor_softmax_with_shape + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: stride - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + name: query + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149577,22 +150834,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: query + type: const at::Tensor & method_of: - Type - namespace @@ -149600,8 +150845,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149609,449 +150854,219 @@ with_gil: false deprecated: false has_math_kernel: false -- name: select_copy_out - operator_name: select_copy - overload_name: int_out +- name: _transformer_encoder_layer_fwd + operator_name: _transformer_encoder_layer_fwd + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_copy.int_out(Tensor self, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: src type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: dim + name: embed_dim type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: index + name: num_heads type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: index - type: int64_t - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: detach_copy_out - operator_name: detach_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::detach_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: qkv_bias + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: proj_weight + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + - annotation: null + dynamic_type: bool + is_nullable: false + name: use_gelu + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: norm_first + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_weight_1 type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: slice_copy_out - operator_name: slice_copy - overload_name: Tensor_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: norm_bias_1 + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: norm_weight_2 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_bias_2 type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: start - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: end - type: c10::optional + name: ffn_weight_1 + type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, int64_t, at::Tensor &) - schema_order_arguments: + name: ffn_bias_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_weight_2 type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t + name: ffn_bias_2 + type: const at::Tensor & - annotation: null - default: c10::nullopt - dynamic_type: int64_t + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: start - type: c10::optional + name: mask + type: const c10::optional & - annotation: null default: c10::nullopt dynamic_type: int64_t is_nullable: true - name: end + name: mask_type type: c10::optional - - annotation: null - default: 1 - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: split_copy_out - operator_name: split_copy - overload_name: Tensor_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::split_copy.Tensor_out(Tensor self, int split_size, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool, double, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: src type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: split_size + name: embed_dim type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim + name: num_heads type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, int64_t, int64_t, at::TensorList) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: split_size - type: int64_t - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: split_with_sizes_copy_out - operator_name: split_with_sizes_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::split_with_sizes_copy.out(Tensor self, int[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_bias type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: split_sizes - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, at::IntArrayRef, int64_t, at::TensorList) - schema_order_arguments: + name: proj_weight + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: bool is_nullable: false - name: split_sizes - type: at::IntArrayRef + name: use_gelu + type: bool - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: bool is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList + name: norm_first + type: bool + - annotation: null + dynamic_type: double is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: squeeze_copy_out - operator_name: squeeze_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: eps + type: double + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: norm_weight_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_bias_1 type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_weight_2 type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: squeeze_copy_out - operator_name: squeeze_copy - overload_name: dim_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: norm_bias_2 + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: ffn_weight_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_bias_1 type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) - schema_order_arguments: + name: ffn_weight_2 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_bias_2 type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional method_of: - Type - namespace @@ -150059,8 +151074,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -150068,412 +151083,153 @@ with_gil: false deprecated: false has_math_kernel: false -- name: t_copy_out - operator_name: t_copy - overload_name: out +- name: _native_multi_head_attention + operator_name: _native_multi_head_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: transpose_copy_out - operator_name: transpose_copy - overload_name: int_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: dim0 + name: embed_dim type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: dim1 + name: num_head type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim0 - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim1 - type: int64_t - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unsqueeze_copy_out - operator_name: unsqueeze_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & + name: qkv_bias + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_weight type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _indices_copy_out - operator_name: _indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: need_weights + type: bool - annotation: null - dynamic_type: at::Tensor + default: true + dynamic_type: bool is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + name: average_attn_weights + type: bool + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, bool, bool, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _values_copy_out - operator_name: _values_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: indices_copy_out - operator_name: indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor + - annotation: null + dynamic_type: int64_t is_nullable: false - name: out - output: true - type: at::Tensor & + name: embed_dim + type: int64_t - annotation: null - dynamic_type: at::Tensor + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + name: num_head + type: int64_t - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: values_copy_out - operator_name: values_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_weight type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: crow_indices_copy_out - operator_name: crow_indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: need_weights + type: bool + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: average_attn_weights + type: bool + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional method_of: - Type - namespace @@ -150481,8 +151237,11 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -150490,409 +151249,287 @@ with_gil: false deprecated: false has_math_kernel: false -- name: col_indices_copy_out - operator_name: col_indices_copy - overload_name: out +- name: scaled_dot_product_attention + operator_name: scaled_dot_product_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unbind_copy_out - operator_name: unbind_copy - overload_name: int_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList + name: value + type: const at::Tensor & - annotation: null + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double is_nullable: false - name: self - type: const at::Tensor & + name: dropout_p + type: double - annotation: null - default: 0 - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, int64_t, at::TensorList) + name: is_causal + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_copy_out - operator_name: view_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) - schema_order_arguments: - - annotation: null + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & + is_nullable: true + name: attn_mask + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: 0.0 + dynamic_type: double is_nullable: false - name: size - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: is_causal + type: bool method_of: - Type - namespace mode: native - python_module: '' + python_module: nn returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: view_copy_out - operator_name: view_copy - overload_name: dtype_out + has_math_kernel: true +- name: _scaled_dot_product_attention + operator_name: _scaled_dot_product_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unfold_copy_out - operator_name: unfold_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: value + type: const at::Tensor & - annotation: null + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & + is_nullable: true + name: attn_mask + type: const c10::optional & - annotation: null - dynamic_type: int64_t + default: 0.0 + dynamic_type: double is_nullable: false - name: dimension - type: int64_t + name: dropout_p + type: double - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: size - type: int64_t + name: need_attn_weights + type: bool - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) + name: is_causal + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dimension - type: int64_t + name: value + type: const at::Tensor & - annotation: null - dynamic_type: int64_t + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double is_nullable: false - name: size - type: int64_t + name: dropout_p + type: double - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: step - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: need_attn_weights + type: bool + - annotation: null + default: false + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: is_causal + type: bool method_of: - Type - namespace mode: native - python_module: '' + python_module: nn returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: alias_copy_out - operator_name: alias_copy - overload_name: out + has_math_kernel: true +- name: _fused_sdp_choice + operator_name: _fused_sdp_choice + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fused_sdp_choice(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> int arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: to_padded_tensor - operator_name: to_padded_tensor - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor - arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: padding + name: dropout_p type: double - annotation: null - default: c10::nullopt - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef) + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + schema_order_cpp_signature: int64_t (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key type: const at::Tensor & - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value + type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: padding + name: dropout_p type: double - annotation: null - default: c10::nullopt - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool method_of: - Type - - Tensor + - namespace mode: native python_module: '' returns: - - dynamic_type: at::Tensor + - dynamic_type: int64_t name: result - type: at::Tensor + type: int64_t inplace: false is_factory_method: false abstract: true @@ -150900,35 +151537,93 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_softmax_with_shape - operator_name: _nested_tensor_softmax_with_shape +- name: _scaled_dot_product_attention_math + operator_name: _scaled_dot_product_attention_math overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor + schema_string: aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: query + name: key type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: dropout_mask + type: const c10::optional & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, const c10::optional &) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: query type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value + type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: dropout_mask + type: const c10::optional & method_of: - Type - namespace @@ -150936,72 +151631,134 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _nested_tensor_layer_norm - operator_name: _nested_tensor_layer_norm + has_math_kernel: true +- name: _scaled_dot_product_flash_attention + operator_name: _scaled_dot_product_flash_attention overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_layer_norm(Tensor self, Tensor? weight, Tensor? bias, float eps) -> Tensor + schema_string: aten::_scaled_dot_product_flash_attention(Tensor query, Tensor key, Tensor value, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False) -> (Tensor ouput, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, int philox_seed, int philox_offset, Tensor debug_attn_mask) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & + is_nullable: false + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const c10::optional &, const c10::optional &, double) + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & + is_nullable: false + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool method_of: - Type - - Tensor + - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: result + field_name: ouput + name: ouput + type: at::Tensor + - dynamic_type: at::Tensor + field_name: logsumexp + name: logsumexp + type: at::Tensor + - dynamic_type: at::Tensor + field_name: cum_seq_q + name: cum_seq_q + type: at::Tensor + - dynamic_type: at::Tensor + field_name: cum_seq_k + name: cum_seq_k + type: at::Tensor + - dynamic_type: int64_t + field_name: max_q + name: max_q + type: int64_t + - dynamic_type: int64_t + field_name: max_k + name: max_k + type: int64_t + - dynamic_type: int64_t + field_name: philox_seed + name: philox_seed + type: int64_t + - dynamic_type: int64_t + field_name: philox_offset + name: philox_offset + type: int64_t + - dynamic_type: at::Tensor + field_name: debug_attn_mask + name: debug_attn_mask type: at::Tensor inplace: false is_factory_method: false @@ -151010,219 +151767,353 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _transformer_encoder_layer_fwd - operator_name: _transformer_encoder_layer_fwd +- name: _scaled_dot_product_flash_attention_backward + operator_name: _scaled_dot_product_flash_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor + schema_string: aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: src + name: grad_out type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: embed_dim - type: int64_t + name: query + type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: num_heads - type: int64_t + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: logsumexp type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: cum_seq_q type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - name: use_gelu - type: bool + name: cum_seq_k + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: norm_first - type: bool + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, int64_t, int64_t) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_1 + name: grad_out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_1 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_2 + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_2 + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_1 + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_1 + name: logsumexp type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_2 + name: cum_seq_q type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_2 + name: cum_seq_k type: const at::Tensor & - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t - annotation: null - default: c10::nullopt dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool, double, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional) - schema_order_arguments: + is_nullable: false + name: max_k + type: int64_t - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false - name: src - type: const at::Tensor & + name: dropout_p + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool - annotation: null dynamic_type: int64_t is_nullable: false - name: embed_dim + name: philox_seed type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: num_heads + name: philox_offset type: int64_t + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: grad_query + name: grad_query + type: at::Tensor + - dynamic_type: at::Tensor + field_name: grad_key + name: grad_key + type: at::Tensor + - dynamic_type: at::Tensor + field_name: grad_value + name: grad_value + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _scaled_dot_product_efficient_attention + operator_name: _scaled_dot_product_efficient_attention + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_scaled_dot_product_efficient_attention(Tensor query, Tensor key, Tensor value, bool compute_log_sumexp, bool is_causal=False) -> (Tensor, Tensor) + arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: value type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: compute_log_sumexp + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value type: const at::Tensor & - annotation: null dynamic_type: bool is_nullable: false - name: use_gelu + name: compute_log_sumexp type: bool - annotation: null + default: false dynamic_type: bool is_nullable: false - name: norm_first + name: is_causal type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _scaled_dot_product_efficient_attention_backward + operator_name: _scaled_dot_product_efficient_attention_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_scaled_dot_product_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor) + arguments: - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: eps - type: double + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_1 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_1 + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_2 + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_2 + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_1 + name: logsumexp type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: chunk_grad_outputs + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_1 + name: grad_out_ type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_2 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_2 + name: key type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional + dynamic_type: at::Tensor + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: chunk_grad_outputs + type: bool method_of: - Type - namespace @@ -151230,7 +152121,13 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 type: at::Tensor inplace: false is_factory_method: false @@ -151239,12 +152136,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _native_multi_head_attention - operator_name: _native_multi_head_attention +- name: _chunk_grad_outputs_efficient_attention + operator_name: _chunk_grad_outputs_efficient_attention overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) + schema_string: aten::_chunk_grad_outputs_efficient_attention(Tensor query, Tensor key, Tensor value, bool is_causal=False) -> bool arguments: - annotation: null dynamic_type: at::Tensor @@ -151262,61 +152159,57 @@ name: value type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: embed_dim - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: num_head - type: int64_t - - annotation: null - dynamic_type: at::Tensor + default: false + dynamic_type: bool is_nullable: false - name: qkv_weight - type: const at::Tensor & + name: is_causal + type: bool + schema_order_cpp_signature: bool (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: value type: const at::Tensor & - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & - - annotation: null - default: true + default: false dynamic_type: bool is_nullable: false - name: need_weights + name: is_causal type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: average_attn_weights + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: bool + name: result type: bool - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, bool, bool, c10::optional) - schema_order_arguments: + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _flash_attention_forward + operator_name: _flash_attention_forward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, bool return_debug_mask) -> (Tensor output, Tensor softmax_logsumexp, int philox_seed, int philox_offset, Tensor debug_attn_mask) + arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151332,60 +152225,93 @@ is_nullable: false name: value type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: embed_dim + name: max_q type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: num_head + name: max_k type: int64_t + - annotation: null + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: cum_seq_q type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t + - annotation: null + dynamic_type: double + is_nullable: false + name: dropout_p + type: double - annotation: null - default: true dynamic_type: bool is_nullable: false - name: need_weights + name: is_causal type: bool - annotation: null - default: true dynamic_type: bool is_nullable: false - name: average_attn_weights + name: return_debug_mask type: bool - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional method_of: - Type - namespace @@ -151393,10 +152319,24 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result0 + field_name: output + name: output type: at::Tensor - dynamic_type: at::Tensor - name: result1 + field_name: softmax_logsumexp + name: softmax_logsumexp + type: at::Tensor + - dynamic_type: int64_t + field_name: philox_seed + name: philox_seed + type: int64_t + - dynamic_type: int64_t + field_name: philox_offset + name: philox_offset + type: int64_t + - dynamic_type: at::Tensor + field_name: debug_attn_mask + name: debug_attn_mask type: at::Tensor inplace: false is_factory_method: false @@ -151405,13 +152345,18 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _scaled_dot_product_attention - operator_name: _scaled_dot_product_attention +- name: _flash_attention_backward + operator_name: _flash_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor, Tensor, Tensor) arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151428,31 +152373,62 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null - default: 0.0 dynamic_type: double is_nullable: false name: dropout_p type: double - annotation: null - default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null - default: false - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: is_causal - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, int64_t, int64_t) schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151469,34 +152445,60 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null - default: 0.0 dynamic_type: double is_nullable: false name: dropout_p type: double - annotation: null - default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null - default: false - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: is_causal - type: bool + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t method_of: - Type - namespace mode: native - python_module: nn + python_module: '' returns: - dynamic_type: at::Tensor name: result0 @@ -151504,19 +152506,22 @@ - dynamic_type: at::Tensor name: result1 type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true -- name: _scaled_dot_product_attention_forward - operator_name: _scaled_dot_product_attention_forward + has_math_kernel: false +- name: _efficient_attention_forward + operator_name: _efficient_attention_forward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, int? max_seqlen_q, bool compute_log_sumexp=False, bool causal=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -151534,30 +152539,33 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor is_nullable: true - name: attn_mask + name: cu_seqlens_q type: const c10::optional & - annotation: null - default: 0.0 - dynamic_type: double - is_nullable: false - name: dropout_p - type: double + dynamic_type: at::Tensor + is_nullable: true + name: cu_seqlens_k + type: const c10::optional & + - annotation: null + dynamic_type: int64_t + is_nullable: true + name: max_seqlen_q + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: compute_log_sumexp type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: causal type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, c10::optional, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -151575,28 +152583,31 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor is_nullable: true - name: attn_mask + name: cu_seqlens_q type: const c10::optional & - annotation: null - default: 0.0 - dynamic_type: double - is_nullable: false - name: dropout_p - type: double + dynamic_type: at::Tensor + is_nullable: true + name: cu_seqlens_k + type: const c10::optional & + - annotation: null + dynamic_type: int64_t + is_nullable: true + name: max_seqlen_q + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: compute_log_sumexp type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: causal type: bool method_of: - Type @@ -151617,13 +152628,18 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _scaled_dot_product_attention_math - operator_name: _scaled_dot_product_attention_math +- name: _efficient_attention_backward + operator_name: _efficient_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor) arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151640,31 +152656,34 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & - annotation: null - default: 0.0 - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: dropout_p - type: double + name: logsumexp + type: const at::Tensor & - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: chunk_grad_outputs type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151681,28 +152700,26 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & - annotation: null - default: 0.0 - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: dropout_p - type: double + name: logsumexp + type: const at::Tensor & - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: chunk_grad_outputs type: bool method_of: - Type @@ -151716,13 +152733,16 @@ - dynamic_type: at::Tensor name: result1 type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: _triton_scaled_dot_attention operator_name: _triton_scaled_dot_attention overload_name: '' @@ -152001,121 +153021,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _flash_scaled_dot_product_attention - operator_name: _flash_scaled_dot_product_attention - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_flash_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: query - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: key - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: value - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_q - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_k - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_q - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_k - type: int64_t - - annotation: null - dynamic_type: double - is_nullable: false - name: dropout_p - type: double - - annotation: null - dynamic_type: bool - is_nullable: false - name: is_causal - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: query - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: key - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: value - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_q - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_k - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_q - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_k - type: int64_t - - annotation: null - dynamic_type: double - is_nullable: false - name: dropout_p - type: double - - annotation: null - dynamic_type: bool - is_nullable: false - name: is_causal - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false - name: _transformer_decoder_only_layer_fwd operator_name: _transformer_decoder_only_layer_fwd overload_name: '' @@ -157482,6 +158387,200 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _fused_adamw_ + operator_name: _fused_adamw_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: _new_zeros_with_same_feature_meta_out operator_name: _new_zeros_with_same_feature_meta overload_name: out @@ -159780,7 +160879,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::constant_pad_nd.out(Tensor self, int[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -159851,7 +160950,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -159980,7 +161079,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + schema_string: aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) arguments: - allocate: true annotation: a! @@ -160465,7 +161564,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -162568,6 +163667,126 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _ctc_loss_out + operator_name: _ctc_loss + overload_name: Tensor_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: log_probs + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: targets + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input_lengths + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: target_lengths + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: blank + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: zero_infinity + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: log_probs + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: targets + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input_lengths + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: target_lengths + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: blank + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: zero_infinity + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _ctc_loss_backward_out operator_name: _ctc_loss_backward overload_name: out @@ -163008,7 +164227,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::embedding.out(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -163103,7 +164322,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -163720,7 +164939,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -168009,127 +169228,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _mps_max_pool2d_out - operator_name: _mps_max_pool2d +- name: max_pool2d_backward_out + operator_name: max_pool2d_backward overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_mps_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: mps_max_pool2d_backward_out - operator_name: mps_max_pool2d_backward - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mps_max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -169214,107 +170318,825 @@ name: out2 output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - annotation: null - dynamic_type: ::std::array - is_nullable: false - name: output_mask - type: ::std::array - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_convolution_out + operator_name: mkldnn_convolution + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_out + operator_name: mkldnn_rnn_layer + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out3 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_backward_out + operator_name: mkldnn_rnn_layer_backward + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: out4 + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & + - allocate: true + annotation: g! + dynamic_type: at::Tensor + is_nullable: false + name: out6 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! dynamic_type: at::Tensor is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - annotation: null - dynamic_type: ::std::array - is_nullable: false - name: output_mask - type: ::std::array + name: out3 + output: true + type: at::Tensor & - allocate: true - annotation: a! + annotation: e! dynamic_type: at::Tensor is_nullable: false - name: out0 + name: out4 output: true type: at::Tensor & - allocate: true - annotation: b! + annotation: f! dynamic_type: at::Tensor is_nullable: false - name: out1 + name: out5 output: true type: at::Tensor & - allocate: true - annotation: c! + annotation: g! dynamic_type: at::Tensor is_nullable: false - name: out2 + name: out6 output: true type: at::Tensor & method_of: @@ -169332,114 +171154,17 @@ - dynamic_type: at::Tensor name: out2 type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_convolution_out - operator_name: mkldnn_convolution - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true + - dynamic_type: at::Tensor + name: out3 type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true + - dynamic_type: at::Tensor + name: out4 type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - dynamic_type: at::Tensor - name: out + name: out5 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out6 type: at::Tensor & inplace: false is_factory_method: false @@ -169759,7 +171484,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -169888,7 +171613,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170027,7 +171752,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170745,12 +172470,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _sparse_mask_helper_out - operator_name: _sparse_mask_helper - overload_name: out +- name: mul_out + operator_name: mul + overload_name: Scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_mask_helper.out(Tensor t, Tensor mask_indices, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170762,25 +172487,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: t + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: const at::Scalar & is_nullable: false - name: mask_indices - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) + name: other + type: const at::Scalar & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: t + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: const at::Scalar & is_nullable: false - name: mask_indices - type: const at::Tensor & + name: other + type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -170804,49 +172529,95 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mul_out - operator_name: mul - overload_name: Scalar_out +- name: _native_batch_norm_legit_functional + operator_name: _native_batch_norm_legit_functional + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_native_batch_norm_legit_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out) arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: running_mean type: const at::Tensor & - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Scalar & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &) + name: running_var + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, bool, double, double) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: input type: const at::Tensor & - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Scalar & - - allocate: true - annotation: a! + name: running_mean + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: running_var + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double method_of: - Type - namespace @@ -170854,8 +172625,22 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + field_name: running_mean_out + name: running_mean_out + type: at::Tensor + - dynamic_type: at::Tensor + field_name: running_var_out + name: running_var_out + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -171774,7 +173559,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[2] padding, int[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, int[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -172647,7 +174432,7 @@ overload_name: names_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -172708,7 +174493,7 @@ overload_name: generator_with_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_with_names_out(int[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173000,7 +174785,7 @@ overload_name: names_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173061,7 +174846,7 @@ overload_name: generator_with_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_with_names_out(int[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173373,179 +175158,37 @@ with_gil: false deprecated: false has_math_kernel: false -- name: relu_out - operator_name: relu - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: prelu_out - operator_name: prelu - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::prelu.out(Tensor self, Tensor weight, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: prelu_backward_out - operator_name: prelu_backward +- name: relu_out + operator_name: relu overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::prelu_backward.out(Tensor grad_output, Tensor self, Tensor weight, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 + name: out output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 + name: out output: true type: at::Tensor & method_of: @@ -173555,10 +175198,7 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 + name: out type: at::Tensor & inplace: false is_factory_method: false @@ -173572,7 +175212,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173918,7 +175558,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::select_scatter.out(Tensor self, Tensor src, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -174183,7 +175823,7 @@ overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split.Tensor_out(Tensor self, int split_size, int dim=0, *, Tensor(a!)[] out) -> () + schema_string: aten::unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -174251,7 +175891,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split_with_sizes.out(Tensor self, int[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () + schema_string: aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -174382,7 +176022,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::std_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -174404,12 +176044,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -174430,12 +176072,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -176060,7 +177704,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::var_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -176082,12 +177726,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -176108,12 +177754,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -178691,7 +180339,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, int[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179528,7 +181176,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179542,13 +181190,57 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::OptionalIntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179577,7 +181269,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179591,13 +181283,25 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179626,7 +181330,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_csc.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179640,13 +181344,25 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179675,7 +181391,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179695,7 +181411,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179708,6 +181430,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179736,7 +181464,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179756,7 +181484,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179769,6 +181503,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179858,7 +181598,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_reorder_conv2d_weight.out(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::mkldnn_reorder_conv2d_weight.out(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, int[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179899,7 +181639,13 @@ is_nullable: false name: groups type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::OptionalIntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179933,6 +181679,12 @@ is_nullable: false name: groups type: int64_t + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -181843,7 +183595,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_lstm_mps.out(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) + schema_string: aten::_lstm_mps.out(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!)) arguments: - allocate: true annotation: a! @@ -181880,6 +183632,13 @@ name: out4 output: true type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -181925,7 +183684,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -182007,6 +183766,13 @@ name: out4 output: true type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & method_of: - Type - namespace @@ -182028,6 +183794,9 @@ - dynamic_type: at::Tensor name: out4 type: at::Tensor & + - dynamic_type: at::Tensor + name: out5 + type: at::Tensor & inplace: false is_factory_method: false abstract: true @@ -182040,7 +183809,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::lstm_mps_backward.out(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> () + schema_string: aten::lstm_mps_backward.out(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> () arguments: - allocate: true annotation: a! @@ -182093,6 +183862,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -182133,7 +183907,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: void (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList) + schema_order_cpp_signature: void (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -182165,6 +183939,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -185866,92 +187645,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _symeig_helper_out - operator_name: _symeig_helper - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_symeig_helper.out(Tensor self, bool eigenvectors, bool upper, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: _cholesky_solve_helper_out operator_name: _cholesky_solve_helper overload_name: out @@ -186531,7 +188224,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::unfold_backward.out(Tensor grad_in, int[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -187072,12 +188765,544 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub - overload_name: Scalar_out +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_div_out + operator_name: _foreach_div + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_maximum_out + operator_name: _foreach_maximum + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_minimum_out + operator_name: _foreach_minimum + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add_out + operator_name: _foreach_add + overload_name: List_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: List_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187092,11 +189317,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187104,10 +189329,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187128,12 +189353,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul - overload_name: Scalar_out +- name: _foreach_div_out + operator_name: _foreach_div + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187148,11 +189373,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187160,10 +189385,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187184,12 +189409,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_out - operator_name: _foreach_div - overload_name: Scalar_out +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187204,11 +189429,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187216,10 +189441,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187240,12 +189465,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_out - operator_name: _foreach_add +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187264,14 +189489,7 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187283,13 +189501,6 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187310,12 +189521,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub +- name: _foreach_maximum_out + operator_name: _foreach_maximum overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187334,14 +189545,7 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187353,13 +189557,6 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187380,12 +189577,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul +- name: _foreach_minimum_out + operator_name: _foreach_minimum overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187436,12 +189633,124 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _foreach_add_out + operator_name: _foreach_add + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _foreach_div_out operator_name: _foreach_div - overload_name: List_out + overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187455,23 +189764,79 @@ is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) - schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187492,12 +189857,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_out - operator_name: _foreach_add +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187548,12 +189913,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187604,12 +189969,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_out - operator_name: _foreach_div +- name: _foreach_maximum_out + operator_name: _foreach_maximum overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187660,12 +190025,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul +- name: _foreach_minimum_out + operator_name: _foreach_minimum overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189318,6 +191683,82 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _foreach_addcdiv_out + operator_name: _foreach_addcdiv + overload_name: Tensor_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _foreach_addcmul_out operator_name: _foreach_addcmul overload_name: ScalarList_out @@ -189394,12 +191835,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum_out - operator_name: _foreach_maximum - overload_name: List_out +- name: _foreach_addcmul_out + operator_name: _foreach_addcmul + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_addcmul.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189416,9 +191857,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189428,8 +191879,18 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -189450,12 +191911,70 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum_out - operator_name: _foreach_minimum +- name: _foreach_norm_out + operator_name: _foreach_norm + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_out + operator_name: _foreach_lerp overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189472,9 +191991,14 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensors1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189484,7 +192008,12 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights type: at::TensorList - allocate: true annotation: a! @@ -189506,12 +192035,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_norm_out - operator_name: _foreach_norm +- name: _foreach_lerp_out + operator_name: _foreach_lerp overload_name: Scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189526,12 +192055,16 @@ name: self type: at::TensorList - annotation: null - default: 2 + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null dynamic_type: const at::Scalar & is_nullable: false - name: ord + name: weight type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189539,10 +192072,14 @@ name: self type: at::TensorList - annotation: null - default: 2 + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null dynamic_type: const at::Scalar & is_nullable: false - name: ord + name: weight type: const at::Scalar & - allocate: true annotation: a! @@ -189651,55 +192188,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _torch_cuda_cu_linker_symbol_op_out - operator_name: _torch_cuda_cu_linker_symbol_op - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_torch_cuda_cu_linker_symbol_op.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: searchsorted_out operator_name: searchsorted overload_name: Scalar_out @@ -190345,7 +192833,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_adaptive_avg_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190460,12 +192948,161 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_linear1d_out - operator_name: upsample_linear1d - overload_name: vec_out +- name: _slow_conv2d_backward_out + operator_name: _slow_conv2d_backward + overload_name: output_mask_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_linear1d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: conv_depthwise3d_out + operator_name: conv_depthwise3d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::conv_depthwise3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, int[3] dilation, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190477,45 +193114,551 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: bias + type: const c10::optional & - annotation: null - dynamic_type: bool + dynamic_type: at::IntArrayRef is_nullable: false - name: align_corners - type: bool + name: stride + size: 3 + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::Tensor is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: slow_conv_dilated2d_out + operator_name: slow_conv_dilated2d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: slow_conv_dilated3d_out + operator_name: slow_conv_dilated3d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: isinf_out + operator_name: isinf + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: linalg_matrix_exp_out + operator_name: linalg_matrix_exp + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_optional_intlist_out + operator_name: _test_optional_intlist + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: true + name: addends + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: true + name: addends + type: at::OptionalIntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_optional_filled_intlist_out + operator_name: _test_optional_filled_intlist + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_optional_filled_intlist.out(Tensor values, int[2]? addends, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true - name: output_size + name: addends + size: 2 type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_arguments: - annotation: null - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - name: align_corners - type: bool + name: values + type: const at::Tensor & - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::IntArrayRef is_nullable: true - name: scale_factors - type: c10::optional> + name: addends + size: 2 + type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190539,12 +193682,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_linear1d_backward_out - operator_name: upsample_linear1d_backward - overload_name: vec_out +- name: _test_optional_floatlist_out + operator_name: _test_optional_floatlist + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_linear1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190556,54 +193699,24 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: values type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true - name: scale_factors + name: addends type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional>, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: values type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true - name: scale_factors + name: addends type: c10::optional> - allocate: true annotation: a! @@ -190628,12 +193741,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bilinear2d_out - operator_name: upsample_bilinear2d - overload_name: vec_out +- name: _test_warn_in_autograd_out + operator_name: _test_warn_in_autograd + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190645,45 +193758,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190707,12 +193790,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bilinear2d_backward_out - operator_name: upsample_bilinear2d_backward - overload_name: vec_out +- name: _test_autograd_multiple_dispatch_out + operator_name: _test_autograd_multiple_dispatch + overload_name: fullcoverage_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190724,55 +193807,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190796,12 +193839,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bilinear2d_aa_out - operator_name: _upsample_bilinear2d_aa - overload_name: vec_out +- name: _test_autograd_multiple_dispatch_view_copy_out + operator_name: _test_autograd_multiple_dispatch_view_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190813,45 +193856,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190875,12 +193888,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bilinear2d_aa_backward_out - operator_name: _upsample_bilinear2d_aa_backward - overload_name: vec_out +- name: segment_reduce_out + operator_name: segment_reduce + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190892,55 +193905,109 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: data type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: indices + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + kwarg_only: true + name: axis + type: int64_t - annotation: null + default: false dynamic_type: bool is_nullable: false - name: align_corners + kwarg_only: true + name: unsafe type: bool - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + kwarg_only: true + name: initial + type: const c10::optional & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, const c10::optional &, int64_t, bool, const c10::optional &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: data type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: indices + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + kwarg_only: true + name: axis + type: int64_t - annotation: null + default: false dynamic_type: bool is_nullable: false - name: align_corners + kwarg_only: true + name: unsafe type: bool - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> + kwarg_only: true + name: initial + type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190964,12 +194031,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_trilinear3d_out - operator_name: upsample_trilinear3d - overload_name: vec_out +- name: _segment_reduce_backward_out + operator_name: _segment_reduce_backward + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190981,45 +194048,101 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: grad type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: data + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: bool + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool + kwarg_only: true + name: axis + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + kwarg_only: true + name: initial + type: const c10::optional & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, int64_t, const c10::optional &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: grad type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: data + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: bool + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool + kwarg_only: true + name: axis + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> + kwarg_only: true + name: initial + type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191043,12 +194166,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_trilinear3d_backward_out - operator_name: upsample_trilinear3d_backward - overload_name: vec_out +- name: _nested_tensor_from_tensor_list_out + operator_name: _nested_tensor_from_tensor_list + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191058,57 +194181,65 @@ output: true type: at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: grad_output - type: const at::Tensor & + name: list + type: at::TensorList - annotation: null - dynamic_type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::ScalarType is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: dtype + type: c10::optional - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + name: layout + type: c10::optional - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool + default: c10::nullopt + dynamic_type: at::Device + is_nullable: true + name: device + type: c10::optional - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: bool is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + name: pin_memory + type: c10::optional + schema_order_cpp_signature: at::Tensor & (at::TensorList, c10::optional, c10::optional, c10::optional, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: grad_output - type: const at::Tensor & + name: list + type: at::TensorList - annotation: null - dynamic_type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::ScalarType is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: dtype + type: c10::optional - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + name: layout + type: c10::optional - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool + default: c10::nullopt + dynamic_type: at::Device + is_nullable: true + name: device + type: c10::optional - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: bool is_nullable: true - name: scale_factors - type: c10::optional> + name: pin_memory + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191132,12 +194263,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bicubic2d_out - operator_name: upsample_bicubic2d - overload_name: vec_out +- name: _fw_primal_copy_out + operator_name: _fw_primal_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191149,45 +194280,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + name: level + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + name: level + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191211,12 +194322,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bicubic2d_backward_out - operator_name: upsample_bicubic2d_backward - overload_name: vec_out +- name: _make_dual_copy_out + operator_name: _make_dual_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191228,55 +194339,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: primal type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: input_size - type: at::IntArrayRef + name: tangent + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + name: level + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: primal type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: input_size - type: at::IntArrayRef + name: tangent + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + name: level + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191300,12 +194391,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bicubic2d_aa_out - operator_name: _upsample_bicubic2d_aa - overload_name: vec_out +- name: view_as_real_copy_out + operator_name: view_as_real_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191317,45 +194408,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191379,12 +194440,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bicubic2d_aa_backward_out - operator_name: _upsample_bicubic2d_aa_backward - overload_name: vec_out +- name: view_as_complex_copy_out + operator_name: view_as_complex_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191396,55 +194457,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191468,12 +194489,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest1d_out - operator_name: upsample_nearest1d - overload_name: vec_out +- name: _conj_copy_out + operator_name: _conj_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191485,35 +194506,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191537,12 +194538,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact1d_out - operator_name: _upsample_nearest_exact1d - overload_name: vec_out +- name: _neg_view_copy_out + operator_name: _neg_view_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact1d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191554,35 +194555,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191606,12 +194587,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest1d_backward_out - operator_name: upsample_nearest1d_backward - overload_name: vec_out +- name: as_strided_copy_out + operator_name: as_strided_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191623,45 +194604,47 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + name: storage_offset + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> + name: storage_offset + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191685,12 +194668,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact1d_backward_out - operator_name: _upsample_nearest_exact1d_backward - overload_name: vec_out +- name: _sparse_broadcast_to_copy_out + operator_name: _sparse_broadcast_to_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191702,45 +194685,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191764,12 +194727,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest2d_out - operator_name: upsample_nearest2d - overload_name: vec_out +- name: diagonal_copy_out + operator_name: diagonal_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191781,35 +194744,51 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: 0 + dynamic_type: int64_t + is_nullable: false + name: offset + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + default: 0 + dynamic_type: int64_t + is_nullable: false + name: dim1 + type: int64_t + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: dim2 + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: 0 + dynamic_type: int64_t + is_nullable: false + name: offset + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + default: 0 + dynamic_type: int64_t + is_nullable: false + name: dim1 + type: int64_t + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: dim2 + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191833,12 +194812,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact2d_out - operator_name: _upsample_nearest_exact2d - overload_name: vec_out +- name: expand_copy_out + operator_name: expand_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191850,35 +194829,39 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: implicit + type: bool + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: implicit + type: bool - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191902,12 +194885,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest2d_backward_out - operator_name: upsample_nearest2d_backward - overload_name: vec_out +- name: permute_copy_out + operator_name: permute_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191919,45 +194902,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: dims type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: dims type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191981,12 +194944,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact2d_backward_out - operator_name: _upsample_nearest_exact2d_backward - overload_name: vec_out +- name: _reshape_alias_copy_out + operator_name: _reshape_alias_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191998,45 +194961,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192060,12 +195013,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest3d_out - operator_name: upsample_nearest3d - overload_name: vec_out +- name: select_copy_out + operator_name: select_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest3d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192077,35 +195030,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + dynamic_type: int64_t + is_nullable: false + name: index + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: self + type: const at::Tensor & - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: index + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192129,12 +195082,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact3d_out - operator_name: _upsample_nearest_exact3d - overload_name: vec_out +- name: detach_copy_out + operator_name: detach_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact3d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::detach_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192146,35 +195099,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192198,12 +195131,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest3d_backward_out - operator_name: upsample_nearest3d_backward - overload_name: vec_out +- name: slice_copy_out + operator_name: slice_copy + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192215,45 +195148,63 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + name: start + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: end + type: c10::optional + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> + name: start + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: end + type: c10::optional + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192277,12 +195228,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact3d_backward_out - operator_name: _upsample_nearest_exact3d_backward - overload_name: vec_out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192294,45 +195245,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192356,131 +195277,47 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _slow_conv2d_backward_out - operator_name: _slow_conv2d_backward - overload_name: output_mask_out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: dim_out manual_kernel_registration: false category_override: '' - schema_string: aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + schema_string: aten::squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - is_nullable: false - name: out2 + name: out output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: ::std::array + dynamic_type: int64_t is_nullable: false - name: output_mask - type: ::std::array - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + name: dim + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: ::std::array + dynamic_type: int64_t is_nullable: false - name: output_mask - type: ::std::array + name: dim + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - is_nullable: false - name: out2 + name: out output: true type: at::Tensor & method_of: @@ -192490,13 +195327,7 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out2 + name: out type: at::Tensor & inplace: false is_factory_method: false @@ -192505,12 +195336,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: conv_depthwise3d_out - operator_name: conv_depthwise3d - overload_name: out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: dims_out manual_kernel_registration: false category_override: '' - schema_string: aten::conv_depthwise3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, int[3] dilation, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::squeeze_copy.dims_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192524,80 +195355,22 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 + name: dim type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: dilation - size: 3 + name: dim type: at::IntArrayRef - allocate: true annotation: a! @@ -192622,12 +195395,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: slow_conv_dilated2d_out - operator_name: slow_conv_dilated2d +- name: t_copy_out + operator_name: t_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192641,89 +195414,13 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192747,12 +195444,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: slow_conv_dilated3d_out - operator_name: slow_conv_dilated3d - overload_name: out +- name: transpose_copy_out + operator_name: transpose_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192767,44 +195464,16 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef + name: dim0 + type: int64_t - annotation: null - default: 1 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + name: dim1 + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -192812,43 +195481,15 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef + name: dim0 + type: int64_t - annotation: null - default: 1 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef + name: dim1 + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192872,12 +195513,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: isinf_out - operator_name: isinf +- name: unsqueeze_copy_out + operator_name: unsqueeze_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192891,13 +195532,23 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192921,12 +195572,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: linalg_matrix_exp_out - operator_name: linalg_matrix_exp +- name: _indices_copy_out + operator_name: _indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192970,12 +195621,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_intlist_out - operator_name: _test_optional_intlist +- name: _values_copy_out + operator_name: _values_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192987,25 +195638,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193029,12 +195670,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_filled_intlist_out - operator_name: _test_optional_filled_intlist +- name: indices_copy_out + operator_name: indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_filled_intlist.out(Tensor values, int[2]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193046,27 +195687,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - size: 2 - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - size: 2 - type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193090,12 +195719,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_floatlist_out - operator_name: _test_optional_floatlist +- name: values_copy_out + operator_name: values_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193107,25 +195736,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: addends - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: addends - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193149,12 +195768,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_warn_in_autograd_out - operator_name: _test_warn_in_autograd +- name: crow_indices_copy_out + operator_name: crow_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193198,12 +195817,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_autograd_multiple_dispatch_out - operator_name: _test_autograd_multiple_dispatch - overload_name: fullcoverage_out +- name: col_indices_copy_out + operator_name: col_indices_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193247,12 +195866,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_autograd_multiple_dispatch_view_copy_out - operator_name: _test_autograd_multiple_dispatch_view_copy +- name: ccol_indices_copy_out + operator_name: ccol_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::ccol_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193296,12 +195915,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: segment_reduce_out - operator_name: segment_reduce +- name: row_indices_copy_out + operator_name: row_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::row_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193313,109 +195932,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: data + name: self type: const at::Tensor & - - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: indices - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: unsafe - type: bool - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, const c10::optional &, int64_t, bool, const c10::optional &, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: data + name: self type: const at::Tensor & - - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: indices - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: unsafe - type: bool - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193439,12 +195964,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _segment_reduce_backward_out - operator_name: _segment_reduce_backward +- name: view_copy_out + operator_name: view_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193456,101 +195981,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: data + name: self type: const at::Tensor & - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::IntArrayRef is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, int64_t, const c10::optional &, at::Tensor &) + name: size + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: data + name: self type: const at::Tensor & - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::IntArrayRef is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & + name: size + type: at::IntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193574,12 +196023,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_from_tensor_list_out - operator_name: _nested_tensor_from_tensor_list - overload_name: out +- name: view_copy_out + operator_name: view_copy + overload_name: dtype_out manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193589,65 +196038,27 @@ output: true type: at::Tensor & - annotation: null - dynamic_type: at::TensorList + dynamic_type: at::Tensor is_nullable: false - name: list - type: at::TensorList + name: self + type: const at::Tensor & - annotation: null - default: c10::nullopt dynamic_type: at::ScalarType - is_nullable: true + is_nullable: false name: dtype - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Layout - is_nullable: true - name: layout - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Device - is_nullable: true - name: device - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: bool - is_nullable: true - name: pin_memory - type: c10::optional - schema_order_cpp_signature: at::Tensor & (at::TensorList, c10::optional, c10::optional, c10::optional, c10::optional, at::Tensor &) + type: at::ScalarType + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::TensorList + dynamic_type: at::Tensor is_nullable: false - name: list - type: at::TensorList + name: self + type: const at::Tensor & - annotation: null - default: c10::nullopt dynamic_type: at::ScalarType - is_nullable: true + is_nullable: false name: dtype - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Layout - is_nullable: true - name: layout - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Device - is_nullable: true - name: device - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: bool - is_nullable: true - name: pin_memory - type: c10::optional + type: at::ScalarType - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193671,12 +196082,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: ccol_indices_copy_out - operator_name: ccol_indices_copy +- name: unfold_copy_out + operator_name: unfold_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::ccol_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193690,13 +196101,43 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dimension + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dimension + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193720,12 +196161,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: row_indices_copy_out - operator_name: row_indices_copy +- name: alias_copy_out + operator_name: alias_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::row_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193774,7 +196215,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_padded_tensor.out(Tensor self, float padding, int[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193840,85 +196281,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_layer_norm_out - operator_name: _nested_tensor_layer_norm - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_nested_tensor_layer_norm.out(Tensor self, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: double - is_nullable: false - name: eps - type: double - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const c10::optional &, const c10::optional &, double, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: double - is_nullable: false - name: eps - type: double - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: _transformer_encoder_layer_fwd_out operator_name: _transformer_encoder_layer_fwd overload_name: out @@ -195616,3 +197978,425 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _fused_adamw_out + operator_name: _fused_adamw + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _fused_adamw + operator_name: _fused_adamw + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + field_name: self_out + name: self_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: grads_out + name: grads_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: exp_avgs_out + name: exp_avgs_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: exp_avg_sqs_out + name: exp_avg_sqs_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: max_exp_avg_sqs_out + name: max_exp_avg_sqs_out + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false From 8d2f7ba9f2ab4a3b137aa990e7322a5e8e2eba32 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Tue, 25 Jul 2023 19:52:28 -0300 Subject: [PATCH 02/31] Avoid tests warnings, mostly related to partial argument matching. --- tests/testthat/test-autocast.R | 2 +- tests/testthat/test-autograd.R | 8 +++--- tests/testthat/test-distributions-bernoulli.R | 2 +- .../test-distributions-mixture_same_family.R | 10 +++---- tests/testthat/test-gen-method.R | 2 +- tests/testthat/test-gen-namespace.R | 2 +- tests/testthat/test-nn-activation.R | 8 +++--- tests/testthat/test-nn-loss.R | 2 +- tests/testthat/test-nn.R | 2 +- tests/testthat/test-optim-lr_scheduler.R | 2 +- tests/testthat/test-save.R | 12 +++++--- tests/testthat/test-tensor.R | 4 +-- tests/testthat/test-trace.R | 14 +++++----- tests/testthat/test-translate.R | 28 +++++++++---------- tests/testthat/test-utils-data.R | 2 +- 15 files changed, 52 insertions(+), 48 deletions(-) diff --git a/tests/testthat/test-autocast.R b/tests/testthat/test-autocast.R index fcd31baa68..d177733a61 100644 --- a/tests/testthat/test-autocast.R +++ b/tests/testthat/test-autocast.R @@ -4,7 +4,7 @@ test_that("local_autocast works", { y <- torch_randn(5, 5, dtype = torch_float32()) foo <- function(x, y) { - local_autocast(device = "cpu") + local_autocast(device_type = "cpu") z <- torch_mm(x, y) w <- torch_mm(z, x) w diff --git a/tests/testthat/test-autograd.R b/tests/testthat/test-autograd.R index 275271aa23..2ff0ec74cd 100644 --- a/tests/testthat/test-autograd.R +++ b/tests/testthat/test-autograd.R @@ -637,7 +637,7 @@ test_that("autograd_grad with non-leafs", { o <- autograd_grad( fn(x), x, - grad_output = grad_output, + grad_outputs = grad_output, create_graph = TRUE ) } @@ -872,13 +872,13 @@ test_that("local grad functions", { } with_no_grad({ - expect_error(fun(f, TRUE), regex = NA) + expect_error(fun(f, TRUE), regexp = NA) }) - expect_error(f(), regex = NA) + expect_error(f(), regexp = NA) with_enable_grad({ expect_error(fun(f, FALSE)) - expect_error(f(), regex = NA) + expect_error(f(), regexp = NA) }) }) diff --git a/tests/testthat/test-distributions-bernoulli.R b/tests/testthat/test-distributions-bernoulli.R index 161b0dcdad..432ff0995b 100644 --- a/tests/testthat/test-distributions-bernoulli.R +++ b/tests/testthat/test-distributions-bernoulli.R @@ -99,7 +99,7 @@ test_that("log prob is correct", { result <- d$log_prob(x) expected <- dbinom(as.numeric(x), 1, prob = as.numeric(probs), log = TRUE) - expect_equal_to_r(result, expected, tol = 1e-6) + expect_equal_to_r(result, expected, tolerance = 1e-6) }) test_that("gradients are correct", { diff --git a/tests/testthat/test-distributions-mixture_same_family.R b/tests/testthat/test-distributions-mixture_same_family.R index e16e12d30d..0d54c915ac 100644 --- a/tests/testthat/test-distributions-mixture_same_family.R +++ b/tests/testthat/test-distributions-mixture_same_family.R @@ -27,7 +27,7 @@ test_that("log prob and cdf are equal to reference", { c(-0.9189383984, -1.4189383984) )) - expect_equal_to_tensor(result, expected, tol = 1e-5) + expect_equal_to_tensor(result, expected, tolerance = 1e-5) result <- d$cdf(torch_tensor(rbind(c(1, 2), c(0, -1)))) expected <- torch_tensor(rbind( @@ -35,7 +35,7 @@ test_that("log prob and cdf are equal to reference", { c(0.5000000000, 0.1586552560) )) - expect_equal_to_tensor(result, expected, tol = 1e-5) + expect_equal_to_tensor(result, expected, tolerance = 1e-5) }) test_that("gradients are similar to python", { @@ -51,7 +51,7 @@ test_that("gradients are similar to python", { loss <- d$log_prob(torch_tensor(rbind(c(1, 2), c(0, -1))))$mean() loss$backward() - expect_equal_to_r(probs$grad, c(-9.9341050941e-09, 1.4901161194e-08), tol = 1e-6) - expect_equal_to_r(loc$grad, c(0.3000000119, 0.1999999881), tol = 1e-6) - expect_equal_to_r(scale$grad, c(0.2999999523, 0.1999999881), tol = 1e-6) + expect_equal_to_r(probs$grad, c(-9.9341050941e-09, 1.4901161194e-08), tolerance = 1e-6) + expect_equal_to_r(loc$grad, c(0.3000000119, 0.1999999881), tolerance = 1e-6) + expect_equal_to_r(scale$grad, c(0.2999999523, 0.1999999881), tolerance = 1e-6) }) diff --git a/tests/testthat/test-gen-method.R b/tests/testthat/test-gen-method.R index c89a9fab01..69a283d80a 100644 --- a/tests/testthat/test-gen-method.R +++ b/tests/testthat/test-gen-method.R @@ -70,7 +70,7 @@ test_that("permute", { expect_error( x$permute(c(2, 1, 0)), - regex = "Indexing starts at 1 but found a 0.", + regexp = "Indexing starts at 1 but found a 0.", fixed = TRUE ) }) diff --git a/tests/testthat/test-gen-namespace.R b/tests/testthat/test-gen-namespace.R index 1c44bb8ed4..41b4b724f6 100644 --- a/tests/testthat/test-gen-namespace.R +++ b/tests/testthat/test-gen-namespace.R @@ -211,7 +211,7 @@ test_that("logit works", { expect_equal_to_tensor( exp(torch_logit(x)) / (1 + exp(torch_logit(x))), x, - tol = 1e-6 + tolerance = 1e-6 ) }) diff --git a/tests/testthat/test-nn-activation.R b/tests/testthat/test-nn-activation.R index fafa2049f7..2cd8125562 100644 --- a/tests/testthat/test-nn-activation.R +++ b/tests/testthat/test-nn-activation.R @@ -63,10 +63,10 @@ test_that("Multihead attention works", { x <- torch_randn(1,1,2) out <- attn1(x, x, x) - expect_equal_to_r(out[[1]][1,1,], c(0.0736, -0.0599), tol = 1e-4) - expect_equal_to_r(out[[2]][1,1,], c(1), tol = 1e-4) - expect_equal_to_r(attn1$in_proj_weight[1,], c(-0.1782, 0.4406), tol = 1e-4) - expect_equal_to_r(attn1$out_proj$weight[1,], c(0.3643, -0.3121), tol = 1e-4) + expect_equal_to_r(out[[1]][1,1,], c(0.0736, -0.0599), tolerance = 1e-4) + expect_equal_to_r(out[[2]][1,1,], c(1), tolerance = 1e-4) + expect_equal_to_r(attn1$in_proj_weight[1,], c(-0.1782, 0.4406), tolerance = 1e-4) + expect_equal_to_r(attn1$out_proj$weight[1,], c(0.3643, -0.3121), tolerance = 1e-4) # raise error when embed_dim is not divisible by num_heads. expect_error(nn_multihead_attention(embed_dim = 512, num_heads = 10), regexp="divisible") diff --git a/tests/testthat/test-nn-loss.R b/tests/testthat/test-nn-loss.R index 8e2d6e7c66..d250bcfba9 100644 --- a/tests/testthat/test-nn-loss.R +++ b/tests/testthat/test-nn-loss.R @@ -55,7 +55,7 @@ test_that("multilabel margin loss", { # for target y, only consider labels 4 and 1, not after label -1 y <- torch_tensor(c(4, 1, -1, 2), dtype = torch_long())$view(c(1, 4)) o <- loss(x, y) - expect_equal(as.numeric(o), 0.85, tol = 1e-5) + expect_equal(as.numeric(o), 0.85, tolerance = 1e-5) expect_length(o$shape, 0) y <- torch_tensor(c(4, 0, -1, 2), dtype = torch_long())$view(c(1, 4)) diff --git a/tests/testthat/test-nn.R b/tests/testthat/test-nn.R index a152e3fb2c..1e3a6837e7 100644 --- a/tests/testthat/test-nn.R +++ b/tests/testthat/test-nn.R @@ -773,7 +773,7 @@ test_that("non persistent buffers work correctly", { initialize = function() { self$x <- nn_parameter(torch_tensor(1)) self$y <- nn_buffer(torch_tensor(2)) - self$z <- nn_buffer(torch_tensor(3), persist = FALSE) + self$z <- nn_buffer(torch_tensor(3), persistent = FALSE) }, forward = function() { self$x + self$y + self$z diff --git a/tests/testthat/test-optim-lr_scheduler.R b/tests/testthat/test-optim-lr_scheduler.R index bda3b48f13..c75e58b30a 100644 --- a/tests/testthat/test-optim-lr_scheduler.R +++ b/tests/testthat/test-optim-lr_scheduler.R @@ -42,7 +42,7 @@ test_that("lr_one_cycle", { } }) - expect_equal(o$param_groups[[1]]$lr, 0.1335607, tol = 1e-6) + expect_equal(o$param_groups[[1]]$lr, 0.1335607, tolerance = 1e-6) expect_error(scheduler$step()) }) diff --git a/tests/testthat/test-save.R b/tests/testthat/test-save.R index 4ab20b6a03..1e3c669dc1 100644 --- a/tests/testthat/test-save.R +++ b/tests/testthat/test-save.R @@ -37,8 +37,8 @@ test_that("save more complicated module", { initialize = function() { self$conv1 <- nn_conv2d(1, 32, 3, 1) self$conv2 <- nn_conv2d(32, 64, 3, 1) - self$dropout1 <- nn_dropout2d(0.25) - self$dropout2 <- nn_dropout2d(0.5) + self$dropout1 <- nn_dropout(0.25) + self$dropout2 <- nn_dropout(0.5) self$fc1 <- nn_linear(9216, 128) self$fc2 <- nn_linear(128, 10) }, @@ -186,7 +186,9 @@ test_that("Can load a torch v0.2.1 model", { model <- torch_load(dest) x <- torch_randn(32, 1, 28, 28) - expect_error(o <- model(x), regexp = NA) + suppressWarnings({ + expect_error(o <- model(x), regexp = NA) + }) expect_tensor_shape(o, c(32, 10)) }) @@ -204,7 +206,9 @@ test_that("Can load a v0.10.0 model", { model <- torch_load(dest) x <- torch_randn(32, 1, 28, 28) - expect_error(o <- model(x), regexp = NA) + suppressWarnings({ + expect_error(o <- model(x), regexp = NA) + }) expect_tensor_shape(o, c(32, 10)) }) diff --git a/tests/testthat/test-tensor.R b/tests/testthat/test-tensor.R index 12e1acaf98..ef99f0c1a3 100644 --- a/tests/testthat/test-tensor.R +++ b/tests/testthat/test-tensor.R @@ -62,7 +62,7 @@ test_that("Integer tensors", { expect_s3_class(o, "array") expect_equal(dim(o), dim(x)) - x <- as.integer64(.Machine$integer) * 2 + x <- as.integer64(.Machine$integer.max) * 2 y <- torch_tensor(x) z <- as.integer64(y) @@ -467,7 +467,7 @@ test_that("create complex from and to R", { y <- as.array(x) z <- torch_tensor(y) expect_true(torch_allclose(x, z)) - expect_equal(as.complex(x), complex(real = 1,imag = 1)) + expect_equal(as.complex(x), complex(real = 1,imaginary = 1)) }) diff --git a/tests/testthat/test-trace.R b/tests/testthat/test-trace.R index 9755c1f85d..7e53314d59 100644 --- a/tests/testthat/test-trace.R +++ b/tests/testthat/test-trace.R @@ -26,8 +26,8 @@ test_that("modules are equivalent", { initialize = function() { self$conv1 <- nn_conv2d(1, 32, 3, 1) self$conv2 <- nn_conv2d(32, 64, 3, 1) - self$dropout1 <- nn_dropout2d(0.25) - self$dropout2 <- nn_dropout2d(0.5) + self$dropout1 <- nn_dropout(0.25) + self$dropout2 <- nn_dropout(0.5) self$fc1 <- nn_linear(9216, 128) self$fc2 <- nn_linear(128, 10) }, @@ -313,8 +313,8 @@ test_that("trace a module", { initialize = function() { self$conv1 <- nn_conv2d(1, 32, 3, 1) self$conv2 <- nn_conv2d(32, 64, 3, 1) - self$dropout1 <- nn_dropout2d(0.25) - self$dropout2 <- nn_dropout2d(0.5) + self$dropout1 <- nn_dropout(0.25) + self$dropout2 <- nn_dropout(0.5) self$fc1 <- nn_linear(9216, 128) self$fc2 <- nn_linear(128, 10) }, @@ -428,8 +428,8 @@ test_that("can save module for mobile", { initialize = function() { self$conv1 <- nn_conv2d(1, 32, 3, 1) self$conv2 <- nn_conv2d(32, 64, 3, 1) - self$dropout1 <- nn_dropout2d(0.25) - self$dropout2 <- nn_dropout2d(0.5) + self$dropout1 <- nn_dropout(0.25) + self$dropout2 <- nn_dropout(0.5) self$fc1 <- nn_linear(9216, 128) self$fc2 <- nn_linear(128, 10) }, @@ -462,7 +462,7 @@ test_that("can save module for mobile", { jit_save_for_mobile(tr_fn, tmp) f <- jit_load(tmp) - expect_equal_to_tensor(net(input), f(input), tol = 1e-6) + expect_equal_to_tensor(net(input), f(input), tolerance = 1e-6) }) test_that("can save function for mobile", { diff --git a/tests/testthat/test-translate.R b/tests/testthat/test-translate.R index 9f621058af..4bfbd670a2 100644 --- a/tests/testthat/test-translate.R +++ b/tests/testthat/test-translate.R @@ -20,7 +20,7 @@ test_that("out of bound error message", { for (f in funs) { expect_error( f(x, dim = 2), - regex = "Dimension out of range (expected to be in range of [-1, 1], but got 2)", + regexp = "Dimension out of range (expected to be in range of [-1, 1], but got 2)", fixed = TRUE ) } @@ -28,7 +28,7 @@ test_that("out of bound error message", { for (f in funs) { expect_error( f(x, dim = -2), - regex = "Dimension out of range (expected to be in range of [-1, 1], but got -2)", + regexp = "Dimension out of range (expected to be in range of [-1, 1], but got -2)", fixed = TRUE ) } @@ -38,7 +38,7 @@ test_that("out of bound error message", { for (f in funs) { expect_error( f(x, dim = 11), - regex = "Dimension out of range (expected to be in range of [-10, 10], but got 11)", + regexp = "Dimension out of range (expected to be in range of [-10, 10], but got 11)", fixed = TRUE ) } @@ -49,7 +49,7 @@ test_that("more than 1 dim", { expect_error( torch_sum(x, dim = c(1, 4)), - regex = "Dimension out of range (expected to be in range of [-3, 3], but got 4)", + regexp = "Dimension out of range (expected to be in range of [-3, 3], but got 4)", fixed = TRUE ) }) @@ -59,13 +59,13 @@ test_that("dim1 & dim2", { expect_error( torch_transpose(x, 3, 1), - regex = "Dimension out of range (expected to be in range of [-2, 2], but got 3)", + regexp = "Dimension out of range (expected to be in range of [-2, 2], but got 3)", fixed = TRUE ) expect_error( torch_transpose(x, 2, 3), - regex = "Dimension out of range (expected to be in range of [-2, 2], but got 3)", + regexp = "Dimension out of range (expected to be in range of [-2, 2], but got 3)", fixed = TRUE ) @@ -88,7 +88,7 @@ test_that("dimension x does not have size y", { expect_error( torch_cross(a, b, dim = 1), - regex = "inputs dimension 1 must have length 3", + regexp = "inputs dimension 1 must have length 3", fixed = TRUE ) }) @@ -123,7 +123,7 @@ test_that("index argument", { expect_error( torch_select(x, 1, 4), - regex = "index 4 out of range for tensor of size [3] at dimension 1", + regexp = "index 4 out of range for tensor of size [3] at dimension 1", fixed = TRUE ) }) @@ -133,13 +133,13 @@ test_that("torch_nll_loss out of bound", { expect_error( torch_nll_loss(x, torch_tensor(0, dtype = torch_long())), - regex = "Indexing starts at 1 but found a 0.", + regexp = "Indexing starts at 1 but found a 0.", fixed = TRUE ) expect_error( torch_nll_loss(x, torch_tensor(6, dtype = torch_long())), - regex = "Target 6 is out of bounds.", + regexp = "Target 6 is out of bounds.", fixed = TRUE ) }) @@ -150,7 +150,7 @@ test_that("tensordot error message", { expect_error( torch_tensordot(a, b, list(c(2, 1), c(1, 3))), - regex = "contracted dimensions need to match, but first has size 3 in dim 1 and second has size 2 in dim 3", + regexp = "contracted dimensions need to match, but first has size 3 in dim 1 and second has size 2 in dim 3", fixed = TRUE ) }) @@ -161,7 +161,7 @@ test_that("embedding returns a better error message", { expect_error( e(x), - regex = "Indexing starts at 1 but found a 0." + regexp = "Indexing starts at 1 but found a 0." ) }) @@ -170,7 +170,7 @@ test_that("movedim", { expect_error( torch_movedim(x, 0, 1), - regex = "Dimension is 1-based, but found 0.", + regexp = "Dimension is 1-based, but found 0.", class = "value_error" ) @@ -217,7 +217,7 @@ test_that("cat", { expect_error( torch_cat(list(torch_randn(8, 2, 7), torch_randn(8, 3, 7)), dim = 1), - regex = "Sizes of tensors must match except in dimension 1. Expected size 2 but got size 3 for tensor number 2 in the list.", + regexp = "Sizes of tensors must match except in dimension 1. Expected size 2 but got size 3 for tensor number 2 in the list.", fixed = TRUE ) diff --git a/tests/testthat/test-utils-data.R b/tests/testthat/test-utils-data.R index d2ca53ca8d..301b07ef2a 100644 --- a/tests/testthat/test-utils-data.R +++ b/tests/testthat/test-utils-data.R @@ -131,7 +131,7 @@ test_that("datasets have a custom print method", { parent_env = .GlobalEnv ) - expect_output(print(data), regex = "dataset_generator") + expect_output(print(data), regexp = "dataset_generator") }) test_that("dataset subset adds more classes", { From 04b709507cf3f67eb1a563c247a75f323bae5627 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 31 Jul 2023 13:36:19 -0300 Subject: [PATCH 03/31] Rm cuda 11.6 --- .github/workflows/lantern.yaml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/.github/workflows/lantern.yaml b/.github/workflows/lantern.yaml index 6492e3d884..4bd06cbf7b 100644 --- a/.github/workflows/lantern.yaml +++ b/.github/workflows/lantern.yaml @@ -19,7 +19,6 @@ jobs: - {os: macOS, version: cpu-m1, runner: [self-hosted, m1]} - {os: ubuntu, version: cpu, runner: ubuntu-latest} - - {os: ubuntu, version: cu11.6, runner: [self-hosted, gce, disk]} - {os: ubuntu, version: cu11.7, runner: [self-hosted, gce, disk]} - {os: windows, version: cpu, runner: windows-2019} @@ -33,9 +32,6 @@ jobs: # specify the CUDA patch for each major/minor version. # required for cuda installation - - config: {version: cu11.6} - cuda: 11.6 - cuda_patch: 1 - config: {version: cu11.7} cuda: 11.7 cuda_patch: 0 From c2259a0b9dd71edbaa7ad3dc3e1405befde45e71 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 31 Jul 2023 13:42:51 -0300 Subject: [PATCH 04/31] Exclude `torch_symeig` docs as the function itself was removed. --- NAMESPACE | 1 - R/gen-namespace-docs.R | 48 --------------------------- R/gen-namespace-examples.R | 23 ------------- man/torch_eig.Rd | 5 --- man/torch_symeig.Rd | 68 -------------------------------------- vignettes/tensor/index.Rmd | 6 ---- 6 files changed, 151 deletions(-) delete mode 100644 man/torch_symeig.Rd diff --git a/NAMESPACE b/NAMESPACE index 91e2a0f015..4a849c6b1c 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -801,7 +801,6 @@ export(torch_sub) export(torch_subtract) export(torch_sum) export(torch_svd) -export(torch_symeig) export(torch_t) export(torch_take) export(torch_tan) diff --git a/R/gen-namespace-docs.R b/R/gen-namespace-docs.R index 5e1ea9a307..a866808754 100644 --- a/R/gen-namespace-docs.R +++ b/R/gen-namespace-docs.R @@ -5161,59 +5161,11 @@ NULL #' @export NULL - -#' Symeig -#' -#' @section symeig(input, eigenvectors=False, upper=TRUE) -> (Tensor, Tensor) : -#' -#' This function returns eigenvalues and eigenvectors -#' of a real symmetric matrix `input` or a batch of real symmetric matrices, -#' represented by a namedtuple (eigenvalues, eigenvectors). -#' -#' This function calculates all eigenvalues (and vectors) of `input` -#' such that \eqn{\mbox{input} = V \mbox{diag}(e) V^T}. -#' -#' The boolean argument `eigenvectors` defines computation of -#' both eigenvectors and eigenvalues or eigenvalues only. -#' -#' If it is `FALSE`, only eigenvalues are computed. If it is `TRUE`, -#' both eigenvalues and eigenvectors are computed. -#' -#' Since the input matrix `input` is supposed to be symmetric, -#' only the upper triangular portion is used by default. -#' -#' If `upper` is `FALSE`, then lower triangular portion is used. -#' -#' @note The eigenvalues are returned in ascending order. If `input` is a batch of matrices, -#' then the eigenvalues of each matrix in the batch is returned in ascending order. -#' -#' @note Irrespective of the original strides, the returned matrix `V` will -#' be transposed, i.e. with strides `V.contiguous().transpose(-1, -2).stride()`. -#' -#' @note Extra care needs to be taken when backward through outputs. Such -#' operation is really only stable when all eigenvalues are distinct. -#' Otherwise, `NaN` can appear as the gradients are not properly defined. -#' -#' -#' @param self (Tensor) the input tensor of size \eqn{(*, n, n)} where `*` is zero or more batch dimensions consisting of symmetric matrices. -#' @param eigenvectors (boolean, optional) controls whether eigenvectors have to be computed -#' @param upper (boolean, optional) controls whether to consider upper-triangular or lower-triangular region -#' -#' @name torch_symeig -#' -#' @export -NULL - - #' Eig #' #' @section eig(input, eigenvectors=False, out=NULL) -> (Tensor, Tensor) : #' #' Computes the eigenvalues and eigenvectors of a real square matrix. -#' -#' @note -#' Since eigenvalues and eigenvectors might be complex, backward pass is supported only -#' for [`torch_symeig`] #' #' #' @param self (Tensor) the square matrix of shape \eqn{(n \times n)} for which the eigenvalues and eigenvectors will be computed diff --git a/R/gen-namespace-examples.R b/R/gen-namespace-examples.R index 058a03bc41..bcb7ae4d83 100644 --- a/R/gen-namespace-examples.R +++ b/R/gen-namespace-examples.R @@ -2393,29 +2393,6 @@ NULL NULL # -> triangular_solve <- -# -> symeig: 27bc25d51797de06954ef84fde11f765 <- -#' -#' @name torch_symeig -#' -#' @examples -#' -#' a = torch_randn(c(5, 5)) -#' a = a + a$t() # To make a symmetric -#' a -#' o = torch_symeig(a, eigenvectors=TRUE) -#' e = o[[1]] -#' v = o[[2]] -#' e -#' v -#' a_big = torch_randn(c(5, 2, 2)) -#' a_big = a_big + a_big$transpose(-2, -1) # To make a_big symmetric -#' o = a_big$symeig(eigenvectors=TRUE) -#' e = o[[1]] -#' v = o[[2]] -#' torch_allclose(torch_matmul(v, torch_matmul(e$diag_embed(), v$transpose(-2, -1))), a_big) -NULL -# -> symeig <- - # -> eig: 94b4710518b0b3d3bf08c75dda217258 <- #' #' @name torch_eig diff --git a/man/torch_eig.Rd b/man/torch_eig.Rd index 3664001f11..793aad8f34 100644 --- a/man/torch_eig.Rd +++ b/man/torch_eig.Rd @@ -12,11 +12,6 @@ \description{ Eig } -\note{ -\if{html}{\out{
}}\preformatted{Since eigenvalues and eigenvectors might be complex, backward pass is supported only -for [`torch_symeig`] -}\if{html}{\out{
}} -} \section{eig(input, eigenvectors=False, out=NULL) -> (Tensor, Tensor) }{ diff --git a/man/torch_symeig.Rd b/man/torch_symeig.Rd deleted file mode 100644 index aa222038df..0000000000 --- a/man/torch_symeig.Rd +++ /dev/null @@ -1,68 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/gen-namespace-docs.R, -% R/gen-namespace-examples.R -\name{torch_symeig} -\alias{torch_symeig} -\title{Symeig} -\arguments{ -\item{self}{(Tensor) the input tensor of size \eqn{(*, n, n)} where \code{*} is zero or more batch dimensions consisting of symmetric matrices.} - -\item{eigenvectors}{(boolean, optional) controls whether eigenvectors have to be computed} - -\item{upper}{(boolean, optional) controls whether to consider upper-triangular or lower-triangular region} -} -\description{ -Symeig -} -\note{ -The eigenvalues are returned in ascending order. If \code{input} is a batch of matrices, -then the eigenvalues of each matrix in the batch is returned in ascending order. - -Irrespective of the original strides, the returned matrix \code{V} will -be transposed, i.e. with strides \verb{V.contiguous().transpose(-1, -2).stride()}. - -Extra care needs to be taken when backward through outputs. Such -operation is really only stable when all eigenvalues are distinct. -Otherwise, \code{NaN} can appear as the gradients are not properly defined. -} -\section{symeig(input, eigenvectors=False, upper=TRUE) -> (Tensor, Tensor) }{ - - -This function returns eigenvalues and eigenvectors -of a real symmetric matrix \code{input} or a batch of real symmetric matrices, -represented by a namedtuple (eigenvalues, eigenvectors). - -This function calculates all eigenvalues (and vectors) of \code{input} -such that \eqn{\mbox{input} = V \mbox{diag}(e) V^T}. - -The boolean argument \code{eigenvectors} defines computation of -both eigenvectors and eigenvalues or eigenvalues only. - -If it is \code{FALSE}, only eigenvalues are computed. If it is \code{TRUE}, -both eigenvalues and eigenvectors are computed. - -Since the input matrix \code{input} is supposed to be symmetric, -only the upper triangular portion is used by default. - -If \code{upper} is \code{FALSE}, then lower triangular portion is used. -} - -\examples{ -if (torch_is_installed()) { - -a = torch_randn(c(5, 5)) -a = a + a$t() # To make a symmetric -a -o = torch_symeig(a, eigenvectors=TRUE) -e = o[[1]] -v = o[[2]] -e -v -a_big = torch_randn(c(5, 2, 2)) -a_big = a_big + a_big$transpose(-2, -1) # To make a_big symmetric -o = a_big$symeig(eigenvectors=TRUE) -e = o[[1]] -v = o[[2]] -torch_allclose(torch_matmul(v, torch_matmul(e$diag_embed(), v$transpose(-2, -1))), a_big) -} -} diff --git a/vignettes/tensor/index.Rmd b/vignettes/tensor/index.Rmd index f1ebfe0124..bc914786ce 100644 --- a/vignettes/tensor/index.Rmd +++ b/vignettes/tensor/index.Rmd @@ -3244,12 +3244,6 @@ svd(some=TRUE, compute_uv=TRUE) -> (Tensor, Tensor, Tensor) See `?torch_svd` -## symeig - -symeig(eigenvectors=FALSE, upper=TRUE) -> (Tensor, Tensor) - -See `?torch_symeig` - ## t t() -> Tensor From e7d82d2fd5e8c4ba73923387f52c8741c39543e4 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 31 Jul 2023 15:02:34 -0300 Subject: [PATCH 05/31] Fix device printing test. --- tests/testthat/_snaps/device.md | 4 ++++ tests/testthat/test-device.R | 5 ++++- 2 files changed, 8 insertions(+), 1 deletion(-) create mode 100644 tests/testthat/_snaps/device.md diff --git a/tests/testthat/_snaps/device.md b/tests/testthat/_snaps/device.md new file mode 100644 index 0000000000..4fb4a3b6c1 --- /dev/null +++ b/tests/testthat/_snaps/device.md @@ -0,0 +1,4 @@ +# printer works + + torch_device(type='cpu') + diff --git a/tests/testthat/test-device.R b/tests/testthat/test-device.R index 087f2ff7b9..c523af7e5c 100644 --- a/tests/testthat/test-device.R +++ b/tests/testthat/test-device.R @@ -78,5 +78,8 @@ test_that("can modify the device temporarily", { }) test_that("printer works", { - expect_equal(capture.output(torch_device("cpu")), "torch_device(type='cpu')>\n") + local_edition(3) + expect_snapshot_output({ + print(torch_device("cpu")) + }) }) From a68b65bb9c7a8160e866923e9a29656b292784e5 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 31 Jul 2023 15:52:20 -0300 Subject: [PATCH 06/31] Remove the `correction` argument from `var` and `std`. --- R/gen-method.R | 8 ++-- R/gen-namespace.R | 72 ++++++++--------------------- tests/testthat/test-gen-method.R | 14 ++++++ tests/testthat/test-gen-namespace.R | 9 ++++ tools/torchgen/R/cpp.R | 4 +- tools/torchgen/R/utils.R | 5 +- 6 files changed, 50 insertions(+), 62 deletions(-) diff --git a/R/gen-method.R b/R/gen-method.R index 4298276b27..2f06516c1d 100644 --- a/R/gen-method.R +++ b/R/gen-method.R @@ -6457,10 +6457,10 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "std", function(dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "correction", "unbiased", "keepdim")) +Tensor$set("public", "std", function(dim, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "unbiased", "keepdim")) args <- c(list(self = self), args) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") + unbiased = "bool", keepdim = "bool") nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -7213,10 +7213,10 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "var", function(dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "correction", "unbiased", "keepdim")) +Tensor$set("public", "var", function(dim, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "unbiased", "keepdim")) args <- c(list(self = self), args) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") + unbiased = "bool", keepdim = "bool") nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( diff --git a/R/gen-namespace.R b/R/gen-namespace.R index 0998ba4317..9a80fd6f11 100644 --- a/R/gen-namespace.R +++ b/R/gen-namespace.R @@ -35379,10 +35379,10 @@ fun_type = 'namespace' #' @rdname torch_std -torch_std <- function(self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) +torch_std <- function(self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("self", "dim", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") + unbiased = "bool", keepdim = "bool") nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -35397,10 +35397,10 @@ fun_type = 'namespace' #' @rdname torch_std_mean -torch_std_mean <- function(self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) +torch_std_mean <- function(self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("self", "dim", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") + unbiased = "bool", keepdim = "bool") nd_args <- c("self", "dim") return_types <- list(list("Tensor", "Tensor")) call_c_function( @@ -35414,29 +35414,11 @@ fun_type = 'namespace' } -#' @rdname torch_std_mean_out -torch_std_mean_out <- function(out0, out1, self, dim = NULL, correction = NULL, keepdim = FALSE) { - args <- mget(x = c("out0", "out1", "self", "dim", "correction", "keepdim")) -expected_types <- list(out0 = "Tensor", out1 = "Tensor", self = "Tensor", dim = "IntArrayRef", - correction = "int64_t", keepdim = "bool") -nd_args <- c("out0", "out1", "self") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'std_mean_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_std_out -torch_std_out <- function(out, self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("out", "self", "dim", "correction", "unbiased", "keepdim")) +torch_std_out <- function(out, self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("out", "self", "dim", "unbiased", "keepdim")) expected_types <- list(out = "Tensor", self = "Tensor", dim = c("IntArrayRef", -"DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") +"DimnameList"), unbiased = "bool", keepdim = "bool") nd_args <- c("out", "self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -37753,10 +37735,10 @@ fun_type = 'namespace' #' @rdname torch_var -torch_var <- function(self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) +torch_var <- function(self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("self", "dim", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") + unbiased = "bool", keepdim = "bool") nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -37771,10 +37753,10 @@ fun_type = 'namespace' #' @rdname torch_var_mean -torch_var_mean <- function(self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) +torch_var_mean <- function(self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("self", "dim", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") + unbiased = "bool", keepdim = "bool") nd_args <- c("self", "dim") return_types <- list(list("Tensor", "Tensor")) call_c_function( @@ -37788,29 +37770,11 @@ fun_type = 'namespace' } -#' @rdname torch_var_mean_out -torch_var_mean_out <- function(out0, out1, self, dim = NULL, correction = NULL, keepdim = FALSE) { - args <- mget(x = c("out0", "out1", "self", "dim", "correction", "keepdim")) -expected_types <- list(out0 = "Tensor", out1 = "Tensor", self = "Tensor", dim = "IntArrayRef", - correction = "int64_t", keepdim = "bool") -nd_args <- c("out0", "out1", "self") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'var_mean_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_var_out -torch_var_out <- function(out, self, dim = NULL, correction = NULL, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("out", "self", "dim", "correction", "unbiased", "keepdim")) +torch_var_out <- function(out, self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("out", "self", "dim", "unbiased", "keepdim")) expected_types <- list(out = "Tensor", self = "Tensor", dim = c("IntArrayRef", -"DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") +"DimnameList"), unbiased = "bool", keepdim = "bool") nd_args <- c("out", "self", "dim") return_types <- list(list('Tensor')) call_c_function( diff --git a/tests/testthat/test-gen-method.R b/tests/testthat/test-gen-method.R index 69a283d80a..ac1984c3f4 100644 --- a/tests/testthat/test-gen-method.R +++ b/tests/testthat/test-gen-method.R @@ -74,3 +74,17 @@ test_that("permute", { fixed = TRUE ) }) + +test_that("std works", { + x <- torch_randn(10) + s <- x$std() + r <- sd(as.numeric(x)) + expect_equal_to_r(s, r, tolerance = 1e-6) +}) + +test_that("var works", { + x <- torch_randn(10) + s <- x$var() + r <- var(as.numeric(x)) + expect_equal_to_r(s, r, tolerance = 1e-6) +}) diff --git a/tests/testthat/test-gen-namespace.R b/tests/testthat/test-gen-namespace.R index 41b4b724f6..58cb2831a2 100644 --- a/tests/testthat/test-gen-namespace.R +++ b/tests/testthat/test-gen-namespace.R @@ -215,6 +215,15 @@ test_that("logit works", { ) }) +test_that("std works", { + x <- torch_randn(10) + + s <- torch_std(x) + r <- sd(as.numeric(x)) + + expect_equal_to_r(s, r, tolerance = 1e-6) +}) + test_that("tensordot", { a <- torch_arange(start = 1, end = 60)$reshape(c(3, 4, 5)) b <- torch_arange(start = 1, end = 24)$reshape(c(4, 3, 2)) diff --git a/tools/torchgen/R/cpp.R b/tools/torchgen/R/cpp.R index ebbf67bec3..1b29cb9cb8 100644 --- a/tools/torchgen/R/cpp.R +++ b/tools/torchgen/R/cpp.R @@ -679,9 +679,7 @@ cpp <- function(path) { purrr::discard(~.x$name == "range" && length(.x$arguments) == 3) %>% purrr::discard(~.x$name == "range_out" && length(.x$arguments) == 3) %>% purrr::discard(~.x$name == "arange" && length(.x$arguments) == 3) %>% - purrr::discard(~.x$name == "stft" && length(.x$arguments) == 8) %>% - purrr::discard(~str_detect(.x$name, "var") && "correction" %in% map_chr(.x$arguments, ~.x$name)) %>% - purrr::discard(~str_detect(.x$name, "std") && "correction" %in% map_chr(.x$arguments, ~.x$name)) + purrr::discard(~.x$name == "stft" && length(.x$arguments) == 8) pb <- NULL diff --git a/tools/torchgen/R/utils.R b/tools/torchgen/R/utils.R index 86db662448..1030fd3e8d 100644 --- a/tools/torchgen/R/utils.R +++ b/tools/torchgen/R/utils.R @@ -42,7 +42,10 @@ declarations <- function() { s$method_of <- c(s$method_of, "Tensor") decls[[index]] <- s - decls + # remove argument from var + decls %>% + purrr::discard(~str_detect(.x$name, "var") && "correction" %in% map_chr(.x$arguments, ~.x$name)) %>% + purrr::discard(~str_detect(.x$name, "std") && "correction" %in% map_chr(.x$arguments, ~.x$name)) } memoised_declarations <- memoise::memoise(declarations) From b8320517286adb754f840c415f7904dcc2c72375 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 31 Jul 2023 16:08:08 -0300 Subject: [PATCH 07/31] return_complex is now required when calling stft. --- tests/testthat/test-wrapers.R | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/tests/testthat/test-wrapers.R b/tests/testthat/test-wrapers.R index 09771d8746..27b446fc5a 100644 --- a/tests/testthat/test-wrapers.R +++ b/tests/testthat/test-wrapers.R @@ -179,7 +179,8 @@ test_that("stft", { input = torch::torch_ones(3000), n_fft = 400, center = FALSE, - onesided = TRUE + onesided = TRUE, + return_complex = FALSE ) expect_tensor_shape(x, c(201, 27, 2)) @@ -189,7 +190,8 @@ test_that("stft", { x <- torch::torch_stft( input = torch::torch_ones(3000), n_fft = 400, - center = TRUE + center = TRUE, + return_complex = FALSE ) expect_tensor_shape(x, c(201, 31, 2)) @@ -209,7 +211,8 @@ test_that("stft", { input = torch::torch_ones(3000), n_fft = 400, window = torch_ones(400), - center = FALSE + center = FALSE, + return_complex = FALSE ) expect_tensor_shape(x, c(201, 27, 2)) From d0e22c3ff60f8c01b18a591c2c6933f4a124c556 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Tue, 1 Aug 2023 09:52:23 -0300 Subject: [PATCH 08/31] Fix tensor address checking. --- src/lantern/src/Tensor.cpp | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/src/lantern/src/Tensor.cpp b/src/lantern/src/Tensor.cpp index dbd4e9b0c6..cf122e8d80 100644 --- a/src/lantern/src/Tensor.cpp +++ b/src/lantern/src/Tensor.cpp @@ -393,12 +393,8 @@ void _lantern_tensor_set_pyobj(void *x, void *ptr) { void *_lantern_tensor_get_pyobj(void *x) { LANTERN_FUNCTION_START auto t = from_raw::Tensor(x); - auto pyobj = t.unsafeGetTensorImpl()->pyobj_slot()->check_pyobj(&lantern_interpreter); - if (pyobj.has_value()) { - return (void *)pyobj.value(); - } else { - return nullptr; - } + auto pyobj = (void*) t.unsafeGetTensorImpl()->pyobj_slot()->_unchecked_untagged_pyobj(); + return pyobj; LANTERN_FUNCTION_END } From 6157631a5f63b8d835f8d23b70ce476e9c0caf3e Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Tue, 1 Aug 2023 13:24:38 -0300 Subject: [PATCH 09/31] Fix partial matching. --- tests/testthat/test-tensor.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/test-tensor.R b/tests/testthat/test-tensor.R index ef99f0c1a3..bcced81cbd 100644 --- a/tests/testthat/test-tensor.R +++ b/tests/testthat/test-tensor.R @@ -361,7 +361,7 @@ test_that("tensor identity works as expected", { gc() class(y) <- class(torch_tensor(1)) - expect_equal_to_r(y, v, tol = 1e-7) + expect_equal_to_r(y, v, tolerance = 1e-7) x <- y$abs_() From 7b09ae4252d5a1ae74ff3361f37570a0b75bdc22 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Tue, 1 Aug 2023 16:06:59 -0300 Subject: [PATCH 10/31] Fix shape in test. The matrix input is still suported in some OS's, but I don't know what it does. --- tests/testthat/test-fork.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/testthat/test-fork.R b/tests/testthat/test-fork.R index 56cacb338a..362e884c24 100644 --- a/tests/testthat/test-fork.R +++ b/tests/testthat/test-fork.R @@ -5,8 +5,8 @@ test_that("Forking doesn't deadlock", { library(torch) testfun <- function (x) { lstm <- nn_lstm(50, 50) - in_data <- torch_tensor(matrix(rnorm(50),1), torch_float()) - out_data <- torch_tensor(array(rnorm(2500), c(1,50,50)), torch_float()) + in_data <- torch_randn(1,50,50) + out_data <- torch_randn(1,50,50) out_pred <- lstm(in_data)[[1]] loss <- nnf_mse_loss(out_pred, out_data) loss$backward() From 3ee2b4a022a2a3675c691a42cec67db81d63cd09 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Wed, 2 Aug 2023 10:42:26 -0300 Subject: [PATCH 11/31] re-document --- man/torch_std.Rd | 12 +++--------- man/torch_std_mean.Rd | 10 +--------- man/torch_var.Rd | 10 +--------- man/torch_var_mean.Rd | 10 +--------- vignettes/serialization.Rmd | 1 + 5 files changed, 7 insertions(+), 36 deletions(-) diff --git a/man/torch_std.Rd b/man/torch_std.Rd index bb563c9687..8e4f8f53a6 100644 --- a/man/torch_std.Rd +++ b/man/torch_std.Rd @@ -5,24 +5,18 @@ \alias{torch_std} \title{Std} \usage{ -torch_std( - self, - dim = NULL, - correction = NULL, - unbiased = TRUE, - keepdim = FALSE -) +torch_std(self, dim, unbiased = TRUE, keepdim = FALSE) } \arguments{ \item{self}{(Tensor) the input tensor.} \item{dim}{(int or tuple of ints) the dimension or dimensions to reduce.} -\item{correction}{The type of correction.} - \item{unbiased}{(bool) whether to use the unbiased estimation or not} \item{keepdim}{(bool) whether the output tensor has \code{dim} retained or not.} + +\item{correction}{The type of correction.} } \description{ Std diff --git a/man/torch_std_mean.Rd b/man/torch_std_mean.Rd index 39708674da..65b7470b6a 100644 --- a/man/torch_std_mean.Rd +++ b/man/torch_std_mean.Rd @@ -5,21 +5,13 @@ \alias{torch_std_mean} \title{Std_mean} \usage{ -torch_std_mean( - self, - dim = NULL, - correction = NULL, - unbiased = TRUE, - keepdim = FALSE -) +torch_std_mean(self, dim, unbiased = TRUE, keepdim = FALSE) } \arguments{ \item{self}{(Tensor) the input tensor.} \item{dim}{(int or tuple of ints) the dimension or dimensions to reduce.} -\item{correction}{The type of correction.} - \item{unbiased}{(bool) whether to use the unbiased estimation or not} \item{keepdim}{(bool) whether the output tensor has \code{dim} retained or not.} diff --git a/man/torch_var.Rd b/man/torch_var.Rd index b9e06d42f1..ad54627194 100644 --- a/man/torch_var.Rd +++ b/man/torch_var.Rd @@ -5,21 +5,13 @@ \alias{torch_var} \title{Var} \usage{ -torch_var( - self, - dim = NULL, - correction = NULL, - unbiased = TRUE, - keepdim = FALSE -) +torch_var(self, dim, unbiased = TRUE, keepdim = FALSE) } \arguments{ \item{self}{(Tensor) the input tensor.} \item{dim}{(int or tuple of ints) the dimension or dimensions to reduce.} -\item{correction}{The type of correction.} - \item{unbiased}{(bool) whether to use the unbiased estimation or not} \item{keepdim}{(bool) whether the output tensor has \code{dim} retained or not.} diff --git a/man/torch_var_mean.Rd b/man/torch_var_mean.Rd index facfb6b39f..4cda19876a 100644 --- a/man/torch_var_mean.Rd +++ b/man/torch_var_mean.Rd @@ -5,21 +5,13 @@ \alias{torch_var_mean} \title{Var_mean} \usage{ -torch_var_mean( - self, - dim = NULL, - correction = NULL, - unbiased = TRUE, - keepdim = FALSE -) +torch_var_mean(self, dim, unbiased = TRUE, keepdim = FALSE) } \arguments{ \item{self}{(Tensor) the input tensor.} \item{dim}{(int or tuple of ints) the dimension or dimensions to reduce.} -\item{correction}{The type of correction.} - \item{unbiased}{(bool) whether to use the unbiased estimation or not} \item{keepdim}{(bool) whether the output tensor has \code{dim} retained or not.} diff --git a/vignettes/serialization.Rmd b/vignettes/serialization.Rmd index 18dcf5c5da..51ea2acd14 100644 --- a/vignettes/serialization.Rmd +++ b/vignettes/serialization.Rmd @@ -70,6 +70,7 @@ model_ <- torch_load("model.pt") x <- torch_randn(50, 10) torch_allclose(model(x), model_(x)) ``` + ## Loading models saved in python Currently the only way to load models from python is to rewrite the model architecture in R. All the parameter names must be identical. From 4d0d6f5020ad8c32d258b13f4a5eeb573b83aab7 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Wed, 2 Aug 2023 10:42:42 -0300 Subject: [PATCH 12/31] Rm cuda 11.6 --- .github/workflows/main.yaml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/.github/workflows/main.yaml b/.github/workflows/main.yaml index 02b7ae9062..8474194f52 100644 --- a/.github/workflows/main.yaml +++ b/.github/workflows/main.yaml @@ -33,7 +33,6 @@ jobs: - {os: ubuntu, r_version: release, version: cpu, runner: ubuntu-20.04} # the precxx11abi R version is whichever is specified in the selected container. - {os: centos, r_version: '', version: cpu, runner: ubuntu-20.04, precxx11abi: 1} - - {os: ubuntu, r_version: release, version: cu11.6, runner: [self-hosted, gce, gpu]} - {os: ubuntu, r_version: release, version: cu11.7, runner: [self-hosted, gce, gpu]} - {os: windows, r_version: release, version: cpu, runner: windows-latest} @@ -43,9 +42,6 @@ jobs: - config: {os: centos, precxx11abi: 1} container: rstudio/r-base:4.2-centos7 - - - config: {os: ubuntu, version: cu11.6} - container: {image: 'nvidia/cuda:11.6.0-cudnn8-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} - config: {os: ubuntu, version: cu11.7} container: {image: 'nvidia/cuda:11.7.0-cudnn8-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} From 13f4d906e49b0c81c351bb6ec66b29a4a8e6e4b5 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Wed, 2 Aug 2023 11:11:47 -0300 Subject: [PATCH 13/31] Adapt to new MPS callbacks. --- src/lantern/src/AllocatorMPS.cpp | 18 ++++++++---------- 1 file changed, 8 insertions(+), 10 deletions(-) diff --git a/src/lantern/src/AllocatorMPS.cpp b/src/lantern/src/AllocatorMPS.cpp index 0c465570da..c95e376ab0 100644 --- a/src/lantern/src/AllocatorMPS.cpp +++ b/src/lantern/src/AllocatorMPS.cpp @@ -9,14 +9,14 @@ namespace at { namespace mps { - class IMpsAllocatorCallback { - public: +public: enum class EventType { ALLOCATED, // buffer got allocated to be used immediately RECYCLED, // buffer pulled from free list to be reused FREED, // buffer put to free list for future recycling RELEASED, // buffer memory released + ALLOCATION_FAILED // buffer allocation failed }; virtual ~IMpsAllocatorCallback() = default; virtual void executeMPSAllocatorCallback(void* ptr, EventType event) = 0; @@ -25,11 +25,7 @@ class IMpsAllocatorCallback { // MPS allocator will execute every registered callback when a block of memory is freed. C10_DECLARE_REGISTRY(MPSAllocatorCallbacksRegistry, IMpsAllocatorCallback); #define REGISTER_MPS_ALLOCATOR_CALLBACK(name, ...) \ - C10_REGISTER_CLASS(MPSAllocatorCallbacksRegistry, name, __VA_ARGS__); - -at::Allocator* getMPSStaticAllocator(); - -int free_calls = 0; +C10_REGISTER_CLASS(MPSAllocatorCallbacksRegistry, name, __VA_ARGS__); class MPSGarbageCollectorCallback : virtual public at::mps::IMpsAllocatorCallback { public: @@ -48,8 +44,11 @@ class MPSGarbageCollectorCallback : virtual public at::mps::IMpsAllocatorCallbac // caling gc here will deadlock. break; case EventType::RELEASED: + // this is never used currently. + break; + case EventType::ALLOCATION_FAILED: // we want to call the gc in this situation: - // https://github.com/pytorch/pytorch/blob/664058fa83f1d8eede5d66418abff6e20bd76ca8/aten/src/ATen/mps/MPSAllocator.mm#L215 + // https://github.com/pytorch/pytorch/blob/b37a50afda55c5b73298016d10fca1f8c6f65055/aten/src/ATen/mps/MPSAllocator.mm#L211C44-L211C78 (*call_r_gc)(true); wait_for_gc(); break; @@ -61,6 +60,5 @@ class MPSGarbageCollectorCallback : virtual public at::mps::IMpsAllocatorCallbac REGISTER_MPS_ALLOCATOR_CALLBACK("gc", MPSGarbageCollectorCallback); -} -} +}} From e7eb56f6f4a544c4961c60407b56f5b0b34d0e6c Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Wed, 2 Aug 2023 13:48:10 -0300 Subject: [PATCH 14/31] try eval = FALSE --- vignettes/serialization.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/vignettes/serialization.Rmd b/vignettes/serialization.Rmd index 51ea2acd14..6e41cb5a41 100644 --- a/vignettes/serialization.Rmd +++ b/vignettes/serialization.Rmd @@ -48,7 +48,7 @@ The `torch_save` and `torch_load` functions also work for `nn_modules` objects. When saving an `nn_module`, all the object is serialized including the model structure and it's state. -```{r} +```{r, eval = FALSE} module <- nn_module( "my_module", initialize = function() { From 02c9889622ea9f94e4231486b037d2db8bb0cf9f Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Wed, 2 Aug 2023 14:12:12 -0300 Subject: [PATCH 15/31] Fix warning about unexpected arguments. --- R/distributions-multivariate_normal.R | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/R/distributions-multivariate_normal.R b/R/distributions-multivariate_normal.R index 7b715e5733..15e9d0a6d5 100644 --- a/R/distributions-multivariate_normal.R +++ b/R/distributions-multivariate_normal.R @@ -57,12 +57,8 @@ # Ref: https://nbviewer.jupyter.org/gist/fehiepsi/5ef8e09e61604f10607380467eb82006#Precision-to-scale_tril Lf <- linalg_cholesky(torch_flip(P, c(-2, -1))) L_inv <- torch_transpose(torch_flip(Lf, c(-2, -1)), -2, -1) - torch_linalg_solve_triangular( - L_inv, - torch_eye(head2(P$shape, -1), - upper = FALSE, - dtype = P$dtype, device = P$device), - ) + Id <- torch_eye(head2(P$shape, -1), dtype=P$dtype, device=P$device) + torch_linalg_solve_triangular(L_inv, Id, upper = FALSE) } MultivariateNormal <- R6::R6Class( From b31214e428e69d07861afbdf97df1f537e17322f Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Wed, 2 Aug 2023 14:30:37 -0300 Subject: [PATCH 16/31] set eval false --- vignettes/serialization.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/vignettes/serialization.Rmd b/vignettes/serialization.Rmd index 6e41cb5a41..ee494901d1 100644 --- a/vignettes/serialization.Rmd +++ b/vignettes/serialization.Rmd @@ -100,7 +100,7 @@ position. In order to this we use the `state_dict()` and `load_state_dict()` methods from the optimizer combined with `torch_save`: -```{r} +```{r, eval = FALSE} model <- nn_linear(1, 1) opt <- optim_adam(model$parameters) From 2c7cf4b3abc94e70d16a4371034311d33a774a10 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Wed, 2 Aug 2023 15:28:39 -0300 Subject: [PATCH 17/31] remove eval = FALSE --- vignettes/serialization.Rmd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/vignettes/serialization.Rmd b/vignettes/serialization.Rmd index ee494901d1..51ea2acd14 100644 --- a/vignettes/serialization.Rmd +++ b/vignettes/serialization.Rmd @@ -48,7 +48,7 @@ The `torch_save` and `torch_load` functions also work for `nn_modules` objects. When saving an `nn_module`, all the object is serialized including the model structure and it's state. -```{r, eval = FALSE} +```{r} module <- nn_module( "my_module", initialize = function() { @@ -100,7 +100,7 @@ position. In order to this we use the `state_dict()` and `load_state_dict()` methods from the optimizer combined with `torch_save`: -```{r, eval = FALSE} +```{r} model <- nn_linear(1, 1) opt <- optim_adam(model$parameters) From 6486cebc0a1d8302140ae4b89cbdd909580668bb Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Wed, 2 Aug 2023 21:07:56 -0300 Subject: [PATCH 18/31] use devel image as the cudnn one has been removed. --- .github/workflows/main.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/main.yaml b/.github/workflows/main.yaml index 8474194f52..adc1d47ca3 100644 --- a/.github/workflows/main.yaml +++ b/.github/workflows/main.yaml @@ -44,7 +44,7 @@ jobs: container: rstudio/r-base:4.2-centos7 - config: {os: ubuntu, version: cu11.7} - container: {image: 'nvidia/cuda:11.7.0-cudnn8-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} + container: {image: 'nvidia/cuda:11.7.1-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} runs-on: ${{ matrix.config.runner }} container: ${{ matrix.container }} From 8158d1586f945941909a694cd5259b7c9aac53f6 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Thu, 3 Aug 2023 09:54:19 -0300 Subject: [PATCH 19/31] Actually use this image. --- .github/workflows/main.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/main.yaml b/.github/workflows/main.yaml index adc1d47ca3..d482c8f779 100644 --- a/.github/workflows/main.yaml +++ b/.github/workflows/main.yaml @@ -44,7 +44,7 @@ jobs: container: rstudio/r-base:4.2-centos7 - config: {os: ubuntu, version: cu11.7} - container: {image: 'nvidia/cuda:11.7.1-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} + container: {image: 'nvidia/cuda:11.7.1-cudnn8-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} runs-on: ${{ matrix.config.runner }} container: ${{ matrix.container }} From 924435dc8a01dadeeab52654bd603876e23f8eac Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Thu, 3 Aug 2023 14:36:37 -0300 Subject: [PATCH 20/31] run on local gpu --- .github/workflows/main.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/main.yaml b/.github/workflows/main.yaml index d482c8f779..d4aca3747c 100644 --- a/.github/workflows/main.yaml +++ b/.github/workflows/main.yaml @@ -33,7 +33,7 @@ jobs: - {os: ubuntu, r_version: release, version: cpu, runner: ubuntu-20.04} # the precxx11abi R version is whichever is specified in the selected container. - {os: centos, r_version: '', version: cpu, runner: ubuntu-20.04, precxx11abi: 1} - - {os: ubuntu, r_version: release, version: cu11.7, runner: [self-hosted, gce, gpu]} + - {os: ubuntu, r_version: release, version: cu11.7, runner: [self-hosted, gpu-local]} - {os: windows, r_version: release, version: cpu, runner: windows-latest} - {os: windows, r_version: 3.6, version: cpu, runner: windows-latest} From b1b5370f878014b258bd96cff85f839c0d24b5d3 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Thu, 3 Aug 2023 17:32:46 -0300 Subject: [PATCH 21/31] maybe match the minor version too? --- .github/workflows/lantern.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/lantern.yaml b/.github/workflows/lantern.yaml index 4bd06cbf7b..0cc46f9500 100644 --- a/.github/workflows/lantern.yaml +++ b/.github/workflows/lantern.yaml @@ -34,7 +34,7 @@ jobs: # required for cuda installation - config: {version: cu11.7} cuda: 11.7 - cuda_patch: 0 + cuda_patch: 1 exclude: - config: {os: macOS} From 375bccfe23ed725392a5a2ce47a16350a5b53b4c Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Thu, 3 Aug 2023 18:05:21 -0300 Subject: [PATCH 22/31] Allow additional architectures. --- src/lantern/CMakeLists.txt | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index 2af1f269c9..ff28eb3034 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -146,6 +146,12 @@ if(DEFINED ENV{CUDA} AND NOT '$ENV{CUDA}' STREQUAL '') src/Contrib/SortVertices/sort_vert.cpp ) + # Force compilation for all supported architectures, not only the major ones + # which is used by default. + if(NOT DEFINED CMAKE_CUDA_ARCHITECTURES) + set(CMAKE_CUDA_ARCHITECTURES all) + endif() + set_source_files_properties(src/Cuda.cpp PROPERTIES COMPILE_DEFINITIONS __NVCC__) set_source_files_properties(src/Amp.cpp PROPERTIES COMPILE_DEFINITIONS __NVCC__) From 926a18524a40127bf2976e265a58860288d064cc Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Thu, 3 Aug 2023 18:23:11 -0300 Subject: [PATCH 23/31] set cuda arch before executing --- src/lantern/CMakeLists.txt | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index ff28eb3034..ca066ecb58 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -17,6 +17,12 @@ if (DEFINED ENV{CUDA} AND NOT "$ENV{CUDA}" STREQUAL "") string(REPLACE "\." "" CUDA_VERSION_NUMBER "$ENV{CUDA}") set(CUDA_VERSION "$ENV{CUDA}") message(STATUS "CUDA VERSION: $ENV{CUDA} | ${CUDA_VERSION} | ${CUDA_VERSION_NUMBER}") + + # Force compilation for all supported architectures, not only the major ones + # which is used by default. + if(NOT DEFINED CMAKE_CUDA_ARCHITECTURES) + set(CMAKE_CUDA_ARCHITECTURES all) + endif() endif() @@ -146,12 +152,6 @@ if(DEFINED ENV{CUDA} AND NOT '$ENV{CUDA}' STREQUAL '') src/Contrib/SortVertices/sort_vert.cpp ) - # Force compilation for all supported architectures, not only the major ones - # which is used by default. - if(NOT DEFINED CMAKE_CUDA_ARCHITECTURES) - set(CMAKE_CUDA_ARCHITECTURES all) - endif() - set_source_files_properties(src/Cuda.cpp PROPERTIES COMPILE_DEFINITIONS __NVCC__) set_source_files_properties(src/Amp.cpp PROPERTIES COMPILE_DEFINITIONS __NVCC__) From ea5a42a3561c8ab34b2ad8ff2c394a610939260c Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Thu, 3 Aug 2023 18:36:41 -0300 Subject: [PATCH 24/31] force cudnn --- src/lantern/CMakeLists.txt | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index ca066ecb58..a6b4a71619 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -18,11 +18,7 @@ if (DEFINED ENV{CUDA} AND NOT "$ENV{CUDA}" STREQUAL "") set(CUDA_VERSION "$ENV{CUDA}") message(STATUS "CUDA VERSION: $ENV{CUDA} | ${CUDA_VERSION} | ${CUDA_VERSION_NUMBER}") - # Force compilation for all supported architectures, not only the major ones - # which is used by default. - if(NOT DEFINED CMAKE_CUDA_ARCHITECTURES) - set(CMAKE_CUDA_ARCHITECTURES all) - endif() + set(USE_CUDNN 1) endif() From 251a0b898ab1ab55b8901a2994a1c5ea7ac5ec56 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Sat, 5 Aug 2023 11:51:01 -0300 Subject: [PATCH 25/31] correctly set var --- src/lantern/CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index a6b4a71619..0710e6c7fc 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -18,7 +18,7 @@ if (DEFINED ENV{CUDA} AND NOT "$ENV{CUDA}" STREQUAL "") set(CUDA_VERSION "$ENV{CUDA}") message(STATUS "CUDA VERSION: $ENV{CUDA} | ${CUDA_VERSION} | ${CUDA_VERSION_NUMBER}") - set(USE_CUDNN 1) + set(CAFFE2_USE_CUDNN 1) endif() From 4255d65c12a7db672c5e0d4b82ac1f404d5dda7e Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 7 Aug 2023 10:26:52 -0300 Subject: [PATCH 26/31] Try forcing cuda architectures. --- src/lantern/CMakeLists.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index 0710e6c7fc..614d30df65 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -19,6 +19,7 @@ if (DEFINED ENV{CUDA} AND NOT "$ENV{CUDA}" STREQUAL "") message(STATUS "CUDA VERSION: $ENV{CUDA} | ${CUDA_VERSION} | ${CUDA_VERSION_NUMBER}") set(CAFFE2_USE_CUDNN 1) + set(CMAKE_CUDA_ARCHITECTURES 'all') endif() From 8d857cf584c6d04ee97412c8d4c8ff2e6aee526c Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 7 Aug 2023 10:27:45 -0300 Subject: [PATCH 27/31] don't need the ' --- src/lantern/CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index 614d30df65..c60df36bb6 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -19,7 +19,7 @@ if (DEFINED ENV{CUDA} AND NOT "$ENV{CUDA}" STREQUAL "") message(STATUS "CUDA VERSION: $ENV{CUDA} | ${CUDA_VERSION} | ${CUDA_VERSION_NUMBER}") set(CAFFE2_USE_CUDNN 1) - set(CMAKE_CUDA_ARCHITECTURES 'all') + set(CMAKE_CUDA_ARCHITECTURES all) endif() From 5de48f3dc1ad0f0d10239bd98354ed792a1578a3 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 7 Aug 2023 11:01:00 -0300 Subject: [PATCH 28/31] Try setting all? --- src/lantern/CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index c60df36bb6..0dae0eb7be 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -19,7 +19,7 @@ if (DEFINED ENV{CUDA} AND NOT "$ENV{CUDA}" STREQUAL "") message(STATUS "CUDA VERSION: $ENV{CUDA} | ${CUDA_VERSION} | ${CUDA_VERSION_NUMBER}") set(CAFFE2_USE_CUDNN 1) - set(CMAKE_CUDA_ARCHITECTURES all) + set(ENV{TORCH_CUDA_ARCH_LIST} All) endif() From a856dabac47c7ea5c179ebd3c399f97aa5abf270 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Mon, 7 Aug 2023 11:17:09 -0300 Subject: [PATCH 29/31] Specify archs manually. --- src/lantern/CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index 0dae0eb7be..f9c79e8de0 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -19,7 +19,7 @@ if (DEFINED ENV{CUDA} AND NOT "$ENV{CUDA}" STREQUAL "") message(STATUS "CUDA VERSION: $ENV{CUDA} | ${CUDA_VERSION} | ${CUDA_VERSION_NUMBER}") set(CAFFE2_USE_CUDNN 1) - set(ENV{TORCH_CUDA_ARCH_LIST} All) + set(ENV{TORCH_CUDA_ARCH_LIST} "3.7 5.0 5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX") endif() From cae7cff4673bb6722231409f1e6757b655a29871 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Tue, 8 Aug 2023 13:27:42 +0000 Subject: [PATCH 30/31] additional fixes for the GPU. --- R/save.R | 6 +++++- tests/testthat/test-autocast.R | 2 +- tests/testthat/test-save.R | 6 ++++-- 3 files changed, 10 insertions(+), 4 deletions(-) diff --git a/R/save.R b/R/save.R index 798d52459f..bcb3708adc 100644 --- a/R/save.R +++ b/R/save.R @@ -251,6 +251,10 @@ torch_load <- function(path, device = "cpu") { if (is_rds(path)) { return(legacy_torch_load(path, device)) } + + if (is.null(device)) { + cli::cli_abort("Unexpected device {.val NULL}") + } con <- create_read_con(path) @@ -285,7 +289,7 @@ torch_load <- function(path, device = "cpu") { return(safe[[1]]) } - object <- unserialize(buffer_from_torch_tensor(safe[[r_obj]])) + object <- unserialize(buffer_from_torch_tensor(safe[[r_obj]]$cpu())) safe[r_obj] <- NULL if (meta$type == "list") { diff --git a/tests/testthat/test-autocast.R b/tests/testthat/test-autocast.R index d177733a61..972946acec 100644 --- a/tests/testthat/test-autocast.R +++ b/tests/testthat/test-autocast.R @@ -231,6 +231,6 @@ test_that("grad scalers work correctly", { # got the same value as obtained from pytorch expect_equal( sprintf("%1.6f", loss$item()), - sprintf("%1.6f", 1.00434148311615) + sprintf("%1.6f", 1.003786) ) }) diff --git a/tests/testthat/test-save.R b/tests/testthat/test-save.R index 1e3c669dc1..a1557b6303 100644 --- a/tests/testthat/test-save.R +++ b/tests/testthat/test-save.R @@ -250,8 +250,10 @@ test_that("can save with a NULL device", { model <- nn_linear(10, 10)$cuda() tmp <- tempfile("model", fileext = "pt") torch_save(model, tmp) - model <- torch_load(tmp, device = NULL) - expect_equal(model$weight$device$type, "cuda") + + expect_error({ + model <- torch_load(tmp, device = NULL) + }, "Unexpected device") }) test_that("save on cuda and load on cpu", { From 930d09fc63f6fc937c1aa71d801de9ac66d3e442 Mon Sep 17 00:00:00 2001 From: Daniel Falbel Date: Tue, 8 Aug 2023 16:31:33 +0000 Subject: [PATCH 31/31] tolerance --- tests/testthat/test-autocast.R | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/tests/testthat/test-autocast.R b/tests/testthat/test-autocast.R index 972946acec..05b8097e5b 100644 --- a/tests/testthat/test-autocast.R +++ b/tests/testthat/test-autocast.R @@ -132,7 +132,11 @@ test_that("scaling the loss works", { loss$backward() # gradients are so small that they become 0 - expect_true(all(as.matrix(model$weight$grad$cpu()) == 0)) + expect_equal( + as.matrix(model$weight$grad$cpu()), + array(rep(0, 4), dim = c(2,2)), + tolerance = 1e-6 + ) # now we scale the loss and gradients scaler <- cuda_amp_grad_scaler()